Genetic markers associated with asd and other childhood developmental delay disorders

ABSTRACT

The present invention relates generally to genetic markers for duplication and/or deletion syndromes, such as Wolf-Hirschhorn syndrome (WHS), in particular to copy number variant genetic markers for selecting a patient for therapy for the particular therapy, or predicting the response of a subject to a particular therapy.

CROSS REFERENCE TO RELATED APPLICATION

This application claims the benefit of priority from U.S. Provisional Application Ser. No. 61/977,462, filed Apr. 9, 2014, the disclosure of which is incorporated by reference herein in its entirety.

STATEMENT REGARDING SEQUENCE LISTING

The Sequence Listing associated with this application is provided in text format in lieu of a paper copy, and is hereby incorporated by reference into the specification in its entirety for all purposes. The name of the text file containing the Sequence Listing is LINE_006_01 WO. The text file is 12.2 MB, was created on Apr. 9, 2015, and is being submitted electronically via EFS-Web.

BACKGROUND OF THE INVENTION

Developmental delay disorders are an ever growing group of disorders. Many disorders of childhood development are associated with aberrant copy number (i.e., gain or loss of copy number) of a particular sub-chromosomal region. Developmental delay disorders encompass a wide range of symptoms, skills, and levels of impairment, or disability, that children with the disorder can have. Autism spectrum disorders are closely related to developmental delay disorders. They comprise a spectrum of complex, heterogeneous, behaviorally-defined group of disorders characterized by impairments in social interaction and communication as well as by repetitive and stereotyped behaviors and interests.

Genetic factors play a substantial role in disorders of childhood development (Abrahams B S, Geschwind D H. Advances in autism genetics: on the threshold of a new neurobiology. Nat Rev Genet 2008; 9:341-55; Matsunami et al. Identification of rare DNA sequence variants in high-risk autism families and their prevalence in a large case/control population. Molecular Autism 5:5 (2014); Matsunami et al. Identification of rare recurrent copy number variants in high-risk autism families and their prevalence in a large ASD population. PLOS one 8(1):e52239 (2013)). Genetic mutations and chromosomal abnormalities that play a role in disorders of childhood development may be deletion or duplication variants, including copy number variants (CNV) or single nucleotide variants.

While there is no known medical treatment for many childhood development disorders, some success has been reported for early intervention with behavioral therapies. Identification of genetic markers and biomarkers for disorders of childhood development would allow earlier identification of the disease. Genetic evaluation of subjects suffering from childhood development disorder may also help predict out comes of both pharmacologic and behavioral therapies. Thus, there is an urgent need for a method of reliably identifying subjects with disorders of childhood development.

Wolf-Hirschhorn Syndrome (WHS) is a developmental delay disorder that exhibits high variability of its associated features. These features include the following: characteristic facial dysmorphology, intellectual disability, growth deficiency, seizures, congenital heart disease, kidney dysfunction, scoliosis, and oligodontia, and others.

WHS is a rare, multi-genetic disorder that results from the deletion of contiguous genes in the distal region of the short arm of chromosome 4. Presentation of the disorder includes: intellectual disability, failure to thrive, seizures, and a characteristic facies. The degree to which these “classic” features as well as other co-morbid conditions present themselves in each patient can vary significantly, thereby requiring that the medical management of this disorder be tailored to an individual's needs. Without the benefit of genetic correlation studies of this syndrome, standard medical care for Wolf-Hirschhorn patients means the running of expensive and sometimes invasive medical tests for each patient in order to determine the best course of action.

There is an increasing body of biochemical and genetic evidence suggesting that mitochondrial dysfunction is involved in the pathology of autism (Legido el al. (2013). Seminars in Pediatric Neurology 20, pp. 163-175), as well as other types of developmental delay (DD) disorders. However, not all individuals with ASD or DD display indicators of oxidative stress or mitochondrial dysfunction. Associated with ASD etiology is a strong genetic component; over 800 genetic changes have been proposed to be involved in the causes for ASD (lossifov et al. (2012) Neuron 74, pp. 285-299). Determination of the genetic changes associated with ASD features in individuals may determine the appropriateness of mitochondrial therapies on an individual basis.

SUMMARY OF THE INVENTION

In one aspect of the invention, the present invention provides a method for determining the presence or absence of a deletion or duplication syndrome in a subject. For example, in one embodiment, a method for determining the presence or absence of a deletion or duplication syndrome associated with developmental delay in a subject is provided, wherein the method provides high subchromosomal resolution of the deletion and/or duplication. In one embodiment, the deletion or duplication syndrome is selected from one or more of the deletion or duplication syndromes set forth at Table A and/or Table B. In a further embodiment, the subject is selected for therapy of the deletion or duplication syndrome if the CNV is present, and is at least about 500 bases in length.

The method in one embodiment comprises probing a sample obtained from the subject for the presence or absence of one or more copy number variants (CNVs) associated with the chromosomal deletion or duplication syndrome, and if the CNV is present, optionally analyzing the size of the deletion or duplication of at least one CNV. In one embodiment, the probing step comprises mixing the sample with five or more oligonucleotides that are substantially complementary to portions of the genomic DNA sequence associated with the deletion or duplication syndrome under conditions suitable for hybridization of the five or more oligonucleotides to their complements or substantial complements; detecting whether hybridization occurs between the five or more oligonucleotides to their complements or substantial complements, or a subset thereof and obtaining hybridization values of the sample based on the detecting step.

The determination of whether the CNV is present or absent, in one embodiment, comprises comparing the hybridization values of the sample to reference hybridization value(s) from at least one training set comprising hybridization value(s) from a sample that is positive for the one or more CNVs, or hybridization value(s) from a sample that is negative for the one or more CNVs. In one embodiment, the comparing step comprises determining a correlation between the hybridization values obtained from the sample and the hybridization value(s) from the at least one training set (which may be included in a database of values or a sample training set). A determination is then made regarding the presence or absence of the at least one CNV followed by an assessment of whether the subject has the chromosomal deletion or duplication syndrome.

In one embodiment, the sample comprises restriction digested double stranded DNA obtained from genomic DNA fragments; restriction digested single stranded DNA obtained from genomic DNA fragments; amplified restriction digested genomic DNA single stranded fragments; amplified restriction digested genomic DNA double stranded fragments; or a combination thereof. In a further embodiment, the sample is free of histone proteins. In even a further embodiment, the amplified restriction digested genomic DNA single stranded fragments comprise a detectable label chemically attached to individual single stranded fragments. In yet a further embodiment, the amplified restriction digested genomic DNA single stranded fragments further comprise adapter sequences. In one embodiment, the adapter sequences are introduced via adapter-specific primers.

In one embodiment, the subject is identified as at risk for a clinical manifestation of the deletion or duplication syndrome if the size of the deletion is greater than or equal to 500 bp. Accordingly, if the size of the deletion or duplication is greater than or equal to 500 bp, the subject is selected for treatment of the deletion or duplication syndrome. Alternatively or additionally, depending on the size of the deletion or duplication, a prediction is made regarding whether the subject will respond to treatment for the deletion or duplication syndrome, for example, treatment of a clinical manifestation of the deletion or duplication syndrome.

The probing step in one embodiment comprises a DNA hybridization assay with oligonucleotides specific for DNA sequences associated with the one or more CNVs. The probing step comprises in one embodiment, polymerase chain reaction (PCR), a microarray assay, a NanoString assay (e.g., nCounter CNV Analysis), a sequencing assay (for example high throughput sequencing, single molecule sequencing, next-generation sequencing, etc.) or a combination thereof.

In one embodiment, the deletion or duplication syndrome is a syndrome wherein the chromosomal deletion or duplication is of a varying length. In one embodiment, the deletion syndrome is selected from the group consisting of Wolf-Hirshhorn (4p) syndrome, 22q11.2 deletion syndrome (DiGeorge syndrome), and 1p36 deletion syndrome. In one embodiment, the duplication syndrome is selected from the group consisting of 1q21.1 duplication syndrome, 8p23.1 duplication syndrome and chromosome 15q duplication syndrome. Where the deletion or duplication syndrome is a syndrome of chromosomal deletion or duplication is of a varying length, the method for selecting the subject for therapy of the syndrome, in one embodiment, comprises measuring the size of the CNV.

In a further embodiment, if the subject is diagnosed with the deletion or duplication syndrome, and is further selected for treatment, the subject is treated for a clinical manifestation of the deletion or duplication syndrome selected from congenital heart disease, seizure, renal disease, intellectual disability, developmental delay, vision loss, blindness, or other condition affecting ears, skin, teeth, or skeletal development; or a combination thereof.

In one embodiment, the deletion syndrome is Wolf-Hirshhorn (4p) syndrome (WHS) and the subject is selected for treatment of a clinical manifestation of WHS, if the CNV at chromosome 4p is greater than 500 bases, greater than 1,000 bases, greater than 100,000 bases, greater than 500,000 bases, greater than 1 Mb, greater than 5 Mb, greater than 10 Mb, or greater than 1 Mb. In one embodiment, the method further comprises treating the subject for the clinical manifestation of WHS. In a further embodiment, the method comprises treating the subject for congenital heart disease.

In yet another aspect of the invention, a method for selecting a subject for treatment of status epilepticus or for predicting the response of a subject to treatment of status epilepticus is provided. In one embodiment, the method comprises detecting in a genetic sample from the subject the presence or absence of a copy number variant (CNV) associated with Wolf-Hirshhom (4p-) syndrome; and detecting the presence or absence in the genetic sample a second CNV selected from the CNVs provided in Table 3, 4, 8-10, 12 and/or 13. In a further embodiment, the method comprises selecting the subject for treatment of status epilepticus if the first and second CNVs are detected.

In a further embodiment, the method comprises detecting the first and second CNVs using two or more sets of oligonucleotides, wherein each set of oligonucleotides is complementary or substantially complementary to at least a portion of the CNV associated with Wolf Hirshhorn (4p-) syndrome, or a CNV provided in Table 3, 4, 8-10, 12 and/or 13. In a yet further embodiment, the two or more sets of oligonucleotides each comprises from about 1 to about 100, or from about 2 to about 75, or from about 5 to 50, or from about 10 two about 25, or from about 15 to about 20 oligonucleotides. In another embodiment, the two or more sets of oligonucleotides comprises about 5, about 10, about 15, about 20, about 25, about 30, about 35, about 40, about 45, or about 50 oligonucleotides. In one embodiment, the two or more sets of oligonucleotides are present on an array, such as a high density microarray. In yet another embodiment, the presence or absence of the CNVs are determined via a nucleic acid hybridization assay selected from a PCR based assay, a NanoString assay (e.g., nCounter CNV Analysis) or a sequencing assay (for example high throughput sequencing, single molecule sequencing, next-generation sequencing, etc.).

In another embodiment, the one or more CNVs are associated with one or more mitochondrial associated genes, for example, one or more of the genes set forth in Table 15, herein. Accordingly, the present invention provides methods for determining the presence or absence of a mitochondrial related disorder, and methods for predicting the likelihood of whether a subject will develop such a disorder, e.g., by probing for one or more CNVs that affect mitochondrial associated genes.

In another embodiment, a method for selecting a subject for mitochondrial therapy is provided. In one embodiment, the method comprises probing a genetic sample from the subject for the presence or absence of at least one copy number variant (CNV) associated with a mitochondrial gene, for example a gene set forth in Table 15. In one embodiment, the probing step comprises mixing the sample with five or more oligonucleotides that are substantially complementary to portions of the genomic DNA sequence associated with the CNV under conditions suitable for hybridization of the five or more oligonucleotides to their complements or substantial complements; detecting whether hybridization occurs between the five or more oligonucleotides to their complements or substantial complements, or a subset thereof and obtaining hybridization values of the sample based on the detecting step. The determination of whether the CNV is present or absent, in one embodiment, comprises comparing the hybridization values of the sample to reference hybridization value(s) from at least one training set comprising hybridization value(s) from a sample that is positive for the one or more CNVs, or hybridization value(s) from a sample that is negative for the one or more CNVs. In one embodiment, the comparing step comprises determining a correlation between the hybridization values obtained from the sample and the hybridization value(s) from the at least one training set (which may be included in a database of values or a sample training set). A determination is then made regarding the presence or absence of the at least one CNV followed by an assessment of whether the subject has the chromosomal deletion or duplication syndrome. The subject is then selected or not-selected for therapy based on the assessment of whether the syndrome is present.

In a further embodiment, if the CNV genetic marker is detected, the subject is selected for mitochondrial therapy and is administered mitochondrial therapy. The mitochondrial therapy, in one embodiment, is selected from an antioxidant, oxygen, arginine, Coenzyme Q10, idebenone, benzoquinone therapeutics (e.g., alpha-tocotrienol quinone (EPI-743) (Edison Pharmaceuticals)), creatine, lipoic acid, dichloroacetate (DCA), citrulline, or a combination thereof. In a further embodiment, if the patient is selected for mitochondrial therapy based on the results of the CNV analysis, the method comprises treating the subject with EPI-743.

In one embodiment, the method for determining whether a subject has a deletion or duplication syndrome (and optionally selecting the subject for treatment of the syndrome) comprising probing for the presence or absence in the genetic sample from the subject for 1, 2, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80, 90, 100, 150, 200, or more CNVs. For example, in the case of a mitochondrial related deletion or duplication disorder, one or more of the CNVs in the genes set forth in Table 15 can be probed for. In another embodiment, the method comprises detecting in the genetic sample from the subject the presence of from 1 to 100, from 2 to 75, from 5 to 50, or from 10 to 25 CNVs. In one embodiment, the method comprises selecting the subject for therapy or predicting that the subject will respond to a therapy if the presence of at least 2, at least 5, at least 10, at least 25, or at least 50 of the CNVs are detected. In one embodiment, the at least one CNV comprises a copy number duplication CNV. In another embodiment, the at least one CNV comprises a copy number deletion CNV. In another embodiment, at least two CNVs are detected, and the at least two CNVs comprise a copy number deletion CNV and a copy number duplication CNV. In one embodiment, the at least one CNV is between about 400 base pairs (bp) to about 250 mega base pairs (Mb), between about 500 bp and 1 Mb, between about 500 bp and about 100 Mb, between about 500 bp and 500,000 bp, between about 500 bp and about 100,000 bp, between about 2 Mb and about 80 Mb, between about 5 Mb and about 40 Mb, or between about 10 Mb and about 20 Mb. The CNV(s) of the one or more mitochondrial associated genes, in one embodiment, is detected using a nucleic acid hybridization assay, for example a PCR based assay, a NanoString assay (e.g., nCounter CNV Analysis) or a sequencing assay (for example high throughput sequencing, single molecule sequencing, next-generation sequencing, etc.).

In one embodiment, the one or more sets of oligonucleotides used to interrogate a sample for whether one or more CNVs are present, are included on an array, such as a high density microarray. See, for example, Manning et al., ACMG CMA Practice Guidelines 2011, incorporated herein by reference in its entirety. In one embodiment, the probes on the array are selected from the probes set forth in the accompanying sequence listing, and correspond to the genome positions set forth in Table 14 from U.S. Provisional Application 61/977,462 and Table 14 from International PCT Publication No. 2014/055915, the disclosure of each of which is incorporated by reference in their entireties.

In another embodiment, the method for selecting a subject for a mitochondrial therapy, or for predicting the response of a subject to a mitochondrial therapy comprises determining the mitochondrial function affected by the one or more mitochondrial disease-associated genes associated with the CNV. In a further embodiment, the subject is treated with a mitochondrial therapy, and the mitochondrial therapy is selected based on the mitochondrial function of the one or more mitochondrial disease-associated genes. In a further embodiment, the mitochondrial function is associated with electron transport or regulation of oxidative stress. In one embodiment, the subject was previously diagnosed with an autism spectrum disorder.

In another embodiment, where a CNV is detected that affects one or more glutamergic or GABAergic signaling genes, methods are provided for determining whether the CNV is present in a subject's sample, and if present, a method is provided for selecting the subject for treatment with a drug targeting a glutamate receptor or a GABA receptor, or a method is provided for predicting the response of a subject to treatment with a drug targeting a glutamate receptor or a GABA receptor. For example, in one embodiment, the method comprising detecting in a genetic sample from the subject the presence or absence of a copy number variant (CNV), wherein the CNV is a CNV affecting one or more glutamatergic or GABAergic signaling genes, and selecting the subject for treatment or predicting that the subject will respond to treatment if the CNV is detected. The determination of whether the CNV is present or absent, in one embodiment, comprises comparing the hybridization values of the sample to reference hybridization value(s) from at least one training set comprising hybridization value(s) from a sample that is positive for the CNV, or hybridization value(s) from a sample that is negative for the CNV (such values may be stored in a database). In one embodiment, the comparing step comprises determining a correlation between the hybridization values obtained from the sample and the hybridization value(s) from the at least one training set. A determination is then made regarding the presence or absence of the at least one CNV.

In a further embodiment, the method comprises treating the subject with a glutamate receptor agonist or antagonist or a GABA receptor agonist or antagonist. In a further embodiment, the method comprises determining the effect of the CNV on the excitatory or inhibitory activity of the subject's neurons. In a further embodiment, the method comprises administering to the subject a receptor agonist if the effect of the CNV is an inhibitory effect. In another embodiment, the method comprises administering to the subject a receptor antagonist if the effect of the CNV is an excitatory effect.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1: Workflow for CNV analysis for samples analyzed on the custom array. The same process was used for both CNAM and PennCNV analyses. All samples used for CNV analysis in this study had to meet the quality control measures described. Only unrelated cases and controls were used for the final statistical analysis.

FIG. 2: Manhattan plot of CNVs called both by PennCNV and CNAM. Association statistics across all regions covered on the Illumina custom array are shown. Since the array used was not a genome-wide array, the width of each chromosome on the plot is not proportional to the chromosome length. Adjacent chromosomes are separated by tick marks.

FIG. 3. UCSC Genome browser view of CNVs in the NRXN1 region. CNVs observed in the vicinity of the NRXN1-alpha transcription start site are shown. Note that most CNVs observed in ASD patients include exon 1 of NRXN1-alpha while only 1 control CNV extends into exon 1. Produced with custom tracks listing CNV calls and uploaded to the genome.ucsc.edu website.

FIG. 4. UCSC Genome Browser View of CNVs in the GABR Region on chromosome 15q12. Duplications were called by both PennCNV and by CNAM in this region, however the number of duplications called by each program differed, with many additional duplications called by CNAM. Produced with custom tracks listing CNV calls and uploaded to the genome.ucsc.edu website.

FIG. 5 is a graph of the number of clinical features exhibited by subjects as a function of deletion size in base pairs.

FIG. 6 is a graph of clinical features exhibited by subjects as a function of the number of genes in 4p deletion.

FIG. 7 is a graph showing the correlation between WHS deletion location and seizures. Those individuals who do not have seizures are shown with an asterisk (*). These individuals all have interstitial deletions that do not encompass the terminal region of the 4p chromosome. All other individuals report having significant numbers of seizures, especially throughout childhood. The boxed region of the chromosome ideogram (top part of figure) shows the chromosomal locations of all deletions illustrated with the bars in the graph below. 35 subjects with pure deletions are shown, with the two critical regions necessary for WHS shown for reference (labeled WHS Critical Region 1 and 2).

FIG. 8 illustrates that CMA data can be correlated with a specific type of clinical manifestation, in this case, congenital heart disease. Black bars indicate subjects with congenital heart disease. Gray bars represent subjects without congenital heart disease.

FIG. 9 shows that subjects with multiple CNV findings were more likely to have status epilepticus than subjects with only the 4p-deletion. Each horizontal bar on the graph represents the size and location of a subject's 4p-deletion as detected by the custom microarray provided herein. Black bars indicate subjects with status epilepticus. Gray bars represent subjects without status epilepticus.

DETAILED DESCRIPTION OF THE INVENTION

The present invention relates generally to genetic markers for developmental delay disorders, and specifically, mitochondrial disorders, disorders associated with chromosomal duplications or chromosomal deletions (for example, chromosomal duplications or chromosomal deletions of mitochondrial associated genes). In particular, in one embodiment, the present copy number variant (CNV) genetic markers provide a diagnostic yield (the percentage of individuals with the diagnosis of the disorder that will have an abnormal genetic test result; equal to sensitivity) of at least about 10-12%, for example at least about 20%-40%, e.g., 25%-35%. In contrast, generic chromosomal microarray technologies currently available are expected to remain in the 5%-7% diagnostic yield range for the developmental disorder portion of these microarrays, or karyotype/FISH assay (that is, 5-7% of the individuals with the disorder that are tested with current technologies will have an abnormal result). Thus, in one embodiment, the present invention represents a 2× increase (5% to more than 10%) in specific diagnostic yield over current diagnostic platforms. In one embodiment, the practice of the present invention employs conventional methods of microbiology, molecular biology, recombinant DNA technique, chemical syntheses, chemical analyses, pharmaceutical preparation, formulation, and delivery, and treatment of patients, within the skill of the art, many of which are described below for the purpose of illustration. Such techniques are explained fully in the literature. See, e.g., Current Protocols in Protein Science, Current Protocols in Molecular Biology or Current Protocols in Immunology, John Wiley & Sons, New York, N.Y. (2009); Ausubel et al., Short Protocols in Molecular Biology, 3^(rd) ed., Wiley & Sons, 1995; Sambrook and Russell, Molecular Cloning: A Laboratory Manual (3rd Edition, 2001); Maniatis et al. Molecular Cloning: A Laboratory Manual (1982); DNA Cloning: A Practical Approach, vol. I & II (D. Glover, ed.); Oligonucleotide Synthesis (N. Gait, ed., 1984); Nucleic Acid Hybridization (B. Hames & S. Higgins, eds., 1985); Transcription and Translation (B. Hames & S. Higgins, eds., 1984); Animal Cell Culture (R. Freshney, ed., 1986); Perbal, A Practical Guide to Molecular Cloning (1984) and other like references.

As used in this specification and the appended claims, the singular forms “a,” “an” and “the” include plural references unless the content clearly dictates otherwise.

Throughout this specification, unless the context requires otherwise, the word “comprise”, or variations such as “comprises” or “comprising”, will be understood to imply the inclusion of a stated element or integer or group of elements or integers but not the exclusion of any other element or integer or group of elements or integers.

Each embodiment in this specification is to be applied mutatis mutandis to every other embodiment unless expressly stated otherwise.

Chromosomal duplication and deletion syndromes are often associated with developmental delay. The present invention provides a means for determining whether a subject's genomic DNA includes a copy number variant (“CNV”) at one or more chromosomal locations. For example, in one embodiment, the present invention provides one or more oligonucleotides that specifically hybridize to chromosomal regions set forth in Tables A and B, below, in order to determine whether a subject has a copy number variant in the particular region(s).

TABLE A Autosomal Copy Number Variations Chromosomal Location Associated condition/clinical features 1p36 1p36 deletion syndrome 1q21 1q21 deletion or duplication syndrome 1q41q42 1q41q42 deletion syndrome 1q43q44 1q43q44 deletion or duplication syndrome 2p16.3 (NRXN1) Neurodevelopmental disorder/autism spectrum disorder 2p16.1p15 2p16.1p15 deletion syndrome 2q21.1 Neurodevelopmental disorder/autism spectrum disorder 2q23.1 (MBD5) Intellectual disability and seizures 2q24.2 (SLC4A10) Neurodevelopmental disorder/autism spectrum disorder 2q33.1 2q33.1 deletion syndrome 2q33.3q35 Autism spectrum disorder 2q37 (HDAC4) 2q37.3 deletion syndrome 3p26.3 (CNTN4) Autism spectrum disorder 3p14.1 (FOXP1) 3p interstitial deletion syndrome 3q29 3q29 deletion or duplication syndrome 4p16.3 Wolf-Hirschhorn syndrome (4p- syndrome) 4p16.1 Proximal 4p deletion syndrome 4q32qter Autism spectrum disorder 4q35 Neurodevelopmental disorder, autism spectrum disorder, and seizures 5p15.3p15.2 Cri-du-chat syndrome 5q14.3q15 (MEF2C) 5q14.2q15 deletion syndrome 6p21.32 (SYNGAP1) Neurodevelopmental disorder/autism spectrum disorder 6q25.2q25.3 6q25.2q25.3 deletion syndrome 7q11.2 Neurodevelopmental disorder, autism spectrum (AUTS2/KIAA0442) disorder, and seizures 7q11.23 Williams syndrome or 7q11.23 duplication syndrome 7q35 (CNTNAP2) Autism spectrum disorder 7q36.2 (DPP6) Autism spectrum disorder 8p23.1 8p23.1 deletion syndrome 8q11.23 Autism spectrum disorder 8q22.1 8q22.1 deletion syndrome 8q24.11q24.13 Langer-Giedion syndrome 9q22.3 9q22.3 deletion syndrome 9q34.3 (EHMT1) Kleefstra syndrome (9q subtelomeric deletion syndrome) 10p15.3 Neurodevelopmental disorder 10p14p13 DiGeorge syndrome 2 (Velocardiofacial syndrome 2) 10q22.3q23.31 10q22.3q23.31 deletion syndrome 11p13 WAGR syndrome 11p11.2 Potocki-Shaffer syndrome 11q13.2 (SHANK2) Autism spectrum disorder 11q23qter Jacobsen syndrome 12p Mosaic tetrasomy 12p (Pallister-Killian syndrome) 12q14 12q14 deletion syndrome Chromosome 13 Trisomy 13 (Patau syndrome) 13q 13q deletion syndrome (partial trisomy 13) 14q23.2q23.3 Intellectual disability and spherocytosis Chromosome 15 Tetrasomy 15/Inverted duplicated chromosome 15 (Isodicentric chromosome 15) syndrome 15q11.2 (UBE3A) Neurodevelopmental disorder/autism spectrum disorder/Angelman syndrome/Prader-Willi syndrome 15q13.3 15q13.3 deletion or duplication syndrome 15q24.1q24.2 15q24.1 deletion syndrome 16p13.3 (A2BP1) Neurodevelopmental disorder, autism spectrum disorder, and seizures

TABLE B X linked copy number variations Chromosomal Location Associated condition/clinical features X chromosome Monosomy X (Turner syndrome)/Klinefelter syndrome/XXY syndrome Xp22.32 (NLGN4X) Autism spectrum disorder Xp22.2 (OFD1) Joubert syndrome/Orofacial digital syndrome/ Simpson-Golabi Bemhel syndrome Xp22.13 (CDKL5) CDKL5-related conditions Xp22.2 (AP1S2) XLID Xp22.11 (PTCHD1) Autism spectrum disorder Xp22.1 (SMS) Snyder-Robinson syndrome Xp22 (RPS6KA3) Coffin-Lowry syndrome Xp21.3 (ARX) X-linked intellectual disability (XLID) Xp21.3p21.2 XLID (IL1RAPL1) Xp21.1 (OTC) Ornithine transcarbamylase deficiency Xp11.4 (CASK) XLID and FG syndrome Xp11.3 (ZNF674) XLID Xp11.23 (FTSJ1) XLID Xp11.23 (PQBP1) XLID Xp11.23 (SYN1) XLID Xp11.23 (ZNF81) XLID Xp11.22 (HUWE1) XLID Xp11.22 (SHROOM4) XLID Xp11.22p11.21 Cornelia de Lange syndrome (SMC1A) Xp11.2 (PHF8) XLID Xp11 (ZNF41) XLID Xp11 XLID (KDM5C/JARID1C) Xq11.1 (ARHGEF9) XLID Xq11.4 XLID (TSPAN7/TM4SF2) Xq12 (OPHN1) XLID Xq13 (DLG3) XLID Xq13.1 (NLGN3) Autism spectrum disorder Xq13.2 Allan-Herndon-Dudley syndrome (SLC16A2/MCT8) Xq21.1 (ATRX) Alpha-thalassemia/X-linked intellectual disabilty syndrome Xq22 XLID (ACSL4/FACL4) Xq22 (NXF5) XLID Xq22 (PLP1) Pelizaeus-Merzbacher disease Xq22.3 (DCX) X-linked lissencephaly Xq22.3 (PAK3) XLID Xq24 (CUL4B) XLID Xq24 (UPF3B) XLID Xq25 (GRIA3) XLID Xq25 (OCRL 1) Occulocerebrorenal syndrome of Lowe Xq25 (ZDHHC9) XLID Xq26.1 (HPRT1) Lesch-Nyhan syndrome Xq26.3 X-linked Angelman-like syndrome (NHE6/SLC9A6) Xq28 (ABCD1) X-linked Adrenoleukodystrophy Xq28 (GDI1) XLID Xq28 (MECP2) Rett syndrome/MECP2-related conditions Xq28 (RAB39B) XLID

Developmental delay disorders are an ever growing group of disorders. Many developmental delay disorders are associated with aberrant copy number (gain or loss of copy number) of a particular subchromasomal region and are known as microdeletion and microduplication syndromes. Various microdeletion and microduplication syndromes are disclosed in Weiss et al. (“Microdeletion and microduplication syndromes” J. of Histochemistry & Cytochemistry 60(5) 346; 2012, incorporated by reference in its entirety for all purposes). In one embodiment, the present invention provides a method and/or assay components (e.g., oligonucleotides that specifically hybridize to CNV regions) for the diagnosis of the microdeletion and/or microduplication syndromes disclosed in Weiss et al., and/or a method and/or assay components to select a patient for the treatment of such microdeletion and/or microduplication syndrome. Specifically, any chromosomal deletion or duplication that results in symptoms such as hypotonia (muscle weakness), intellectual disability, dysmorphic physical features, repetitive behaviors is included under the umbrella of developmental delay conditions that can be detected using the present invention. Specific examples include, but are not limited to, the disorders set forth in Tables A and B and specifically, ASD, chromosome 22q13.3 deletion syndrome, 22q11.2 deletion syndrome (DiGeorge syndrome), 1p36 deletion syndrome, Prader-Willi syndrome, Angelman syndrome, chromosome 1p36 deletion syndrome, Wolf-Hirschhorn Syndrome (also known as chromosome 4p-Syndrome), 1q21.1 duplication syndrome, and chromosome 15q duplication syndrome.

Childhood developmental delay disorders may also include, but are not limited to, Rett syndrome, Noonan/Costello/CFC syndromes, Tuberous sclerosis, ADHD, developmental delay (DD), Tourette syndrome, and Dyslexia. The OMIM web site (internet address can be found at ncbi.nlm.nih.gov/omim) keeps an updated list of disorders and a description of the specific genotype identified, that can be accessed by the skilled person.

The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition—Text Revision currently defines five disorders, sometimes called pervasive developmental disorders (PDDs), as ASD. These include: Autistic disorder (classic autism), Asperger's disorder (Asperger syndrome (AS)), Pervasive developmental disorder not otherwise specified (PDD-NOS), Rett's disorder (Rett syndrome), and Childhood disintegrative disorder (CDD). It is noted that the majority of Rett syndrome cases are known to be caused by mutations in either the MeCP2 gene or the CDKL5 gene and it is anticipated that updated revisions of the Diagnostic and Statistical Manual of Mental Disorders will classify Rett syndrome separately from ASD. Therefore, in certain embodiments, ASD does not include Rett syndrome. However, as provided in Table B, the present invention is useful for selecting a patient for the diagnosis of Rett syndrome and or selecting a patient for the treatment of Rett syndrome. Autism shall be understood as any condition of impaired social interaction and communication with restricted repetitive and stereotyped patterns of behavior, interests and activities present before the age of 3, to the extent that health may be impaired. AS is distinguished from autistic disorder by the lack of a clinically significant delay in language development in the presence of the impaired social interaction and restricted repetitive behaviors, interests, and activities that characterize ASD. PDD-NOS is used to categorize individuals who do not meet the strict criteria for autism but who come close, either by manifesting atypical autism or by nearly meeting the diagnostic criteria in two or three of the key areas.

In one aspect of the invention, the present invention provides a method of determining the presence or absence of a deletion or duplication syndrome in a subject. In one embodiment, the deletion or duplication syndrome is selected from one or more of the deletion or duplication syndromes set forth at Table A and/or Table B. In a further embodiment, the subject is selected for therapy of the deletion or duplication syndrome if the CNV is present, and is at least about 500 bases in length.

The method in one embodiment comprises probing a sample obtained from the subject for the presence or absence of one or more copy number variants (CNVs) associated with the chromosomal deletion or duplication syndrome, and if the CNV is present, optionally analyzing the size of the deletion or duplication of at least one CNV. In one embodiment, the probing step comprises mixing the sample with five or more oligonucleotides that are substantially complementary to portions of the genomic DNA sequence associated with the deletion or duplication syndrome under conditions suitable for hybridization of the five or more oligonucleotides to their complements or substantial complements; detecting whether hybridization occurs between the five or more oligonucleotides to their complements or substantial complements, or a subset thereof and obtaining hybridization values of the sample based on the detecting step.

The determination of whether the CNV is present or absent, in one embodiment, comprises comparing the hybridization values of the sample to reference hybridization value(s) from at least one training set comprising hybridization value(s) from a sample that is positive for the one or more CNVs, or hybridization value(s) from a sample that is negative for the one or more CNVs. In one embodiment, the comparing step comprises determining a correlation between the hybridization values obtained from the sample and the hybridization value(s) from the at least one training set (which may be included in a database of values or a sample training set). A determination is then made regarding the presence or absence of the at least one CNV followed by an assessment of whether the subject has the chromosomal deletion or duplication syndrome.

In one embodiment, the sample comprises restriction digested double stranded DNA obtained from genomic DNA fragments; restriction digested single stranded DNA obtained from genomic DNA fragments; amplified restriction digested genomic DNA single stranded fragments; amplified restriction digested genomic DNA double stranded fragments; or a combination thereof. In a further embodiment, the sample is free of histone proteins. In even a further embodiment, the amplified restriction digested genomic DNA single stranded fragments comprise a detectable label chemically attached to individual single stranded fragments. In yet a further embodiment, the amplified restriction digested genomic DNA single stranded fragments further comprise adapter sequences. In one embodiment, the adapter sequences are introduced via adapter-specific primers.

The present invention also provides methods for selecting a subject for a treatment or predicting the response of a subject to a treatment for a childhood development disorder and specifically a duplication or deletion syndrome (e.g., a duplication or deletion syndrome affecting gene associated with mitochondrial function). Treatments for a childhood development disorder encompassed by the methods provided herein include both pharmacological treatments and behavioral treatments. For example, if the CNV is present and the size of the duplication or deletion is greater than or equal to about 500 bp, the subject is diagnosed with the deletion or duplication syndrome and/or is selected for treatment of the syndrome. Alternatively or additionally, if the CNV is present and the size of the duplication or deletion is greater than or equal to about 500 bp, it is predicted that the subject will respond to treatment of the deletion or duplication syndrome, for example, treatment of a clinical manifestation of the deletion or duplication syndrome (e.g., a clinical manifestation of WHS).

The at least one CNV, in one embodiment, is detected using a nucleic acid hybridization assay, for example a genomic DNA hybridization assay with oligonucleotides specific for the at least one CNV. The nucleic acid hybridization assay selected from a PCR based assay, a NanoString assay (e.g., nCounter CNV Analysis) or a sequencing assay (for example high throughput sequencing, single molecule sequencing, next-generation sequencing, etc.), or a combination thereof.

In another embodiment, the one or more CNVs is associated with one or more mitochondrial associated genes, for example, one or more of the genes set forth in Table 15, herein. Accordingly, the present invention provides methods for determining the presence or absence of a mitochondrial related disorder, and methods for predicting the likelihood of whether a subject will develop such a disorder, e.g., by probing for one or more CNVs that affect mitochondrial associated genes.

In another embodiment, a method for selecting a subject for mitochondrial therapy is provided. In one embodiment, the method comprises probing a genetic sample from the subject for the presence or absence of at least one copy number variant (CNV) associated with a mitochondrial gene, for example a gene set forth in Table 15. In one embodiment, the probing step comprises mixing the sample with five or more oligonucleotides that are substantially complementary to portions of the genomic DNA sequence associated with the deletion or duplication syndrome under conditions suitable for hybridization of the five or more oligonucleotides to their complements or substantial complements; detecting whether hybridization occurs between the five or more oligonucleotides to their complements or substantial complements, or a subset thereof and obtaining hybridization values of the sample based on the detecting step. The determination of whether the CNV is present or absent, in one embodiment, comprises comparing the hybridization values of the sample to reference hybridization value(s) from at least one training set comprising hybridization value(s) from a sample that is positive for the one or more CNVs, or hybridization value(s) from a sample that is negative for the one or more CNVs. In one embodiment, the comparing step comprises determining a correlation between the hybridization values obtained from the sample and the hybridization value(s) from the at least one training set (which may be included in a database of values or a sample training set). A determination is then made regarding the presence or absence of the at least one CNV followed by an assessment of whether the subject has the chromosomal deletion or duplication syndrome.

In a further embodiment, if the CNV genetic marker is detected, the subject is selected for mitochondrial therapy and is administered mitochondrial therapy. Categories of mitochondrial functions are instructive as to the type of therapy to employ. For example, categories of mitochondrial function include but are not limited to, NADH dehydrogenase ubiquinone, ATP5 (F1 Complex), cytochrome c reductase, mitochondrial solute/metabolite carriers, mitochondrial ATPases, thioredoxin, ribosomal complex proteins, creatinine kinases, glutathione S transferase family proteins, mitochondrial nucleotidase, OXPHOS proteins, ATP Binding Cassette (ABC) transporters, humanin family of mitochondrial peptides, and pathways or processes such as electron transport, regulation of oxidative stress, apoptosis, fatty acid synthesis, heme biosynthesis, mitochondrial maintenance, and immune responses. In one embodiment, the type of mitochondrial therapy selected for the subject is dependent on the type of function associated with the one or more mitochondrial genes having one or more CNV. The mitochondrial therapy, in one embodiment, is selected from an antioxidant, oxygen, arginine, Coenzyme Q10, idebenone, benzoquinone therapeutics (e.g., alpha-tocotrienol quinone (EPI-743) (Edison Pharmaceuticals)), creatine, lipoic acid, dichloroacetate (DCA), citrulline, or a combination thereof. In a further embodiment, if the patient is selected for mitochondrial therapy based on the results of the CNV analysis, the method comprises treating the subject with quinone (EPI-743) (Edison Pharmaceutical's).

In one embodiment, the method for selecting a subject for a deletion or duplication syndrome therapy or for predicting the response of a subject to a deletion or duplication syndrome therapy comprises detecting the presence or absence in the genetic sample from the subject the presence of 1, 2, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80, 90, 100, 150, 200, or more CNVs.

In one embodiment, the present invention provides a method for selecting a subject for a mitochondrial therapy. In a further embodiment, the subject has previously been diagnosed with one or more disorders, a developmental delay disorder. In a further embodiment, the development disorder is characterized as an ASD. In one embodiment, the method comprises detecting in a genetic sample from the subject the presence or absence of at least one CNV, wherein the at least one CNV is of one or more mitochondrial associated genes, and selecting the subject for mitochondrial therapy if the at least one CNV is detected. In one embodiment, the method comprises detecting in the genetic sample from the subject, the presence of from 1 to 100, from 2 to 75, from 5 to 50, or from 10 to 25 CNVs of one or more mitochondrial disease-associated genes. In one embodiment, the method comprises selecting the subject for mitochondrial therapy if the presence of at least 2, at least 5, at least 10, at least 25, or at least 50 of the CNVs are detected. In one embodiment, the least one CNV is detected using one or more sets of oligonucleotides. In one embodiment, the one or more sets of oligonucleotides are present on an array, such as a high density microarray or are used in an alternative hybridization assay such as a NanoString or genomic sequencing assay.

The methods provided herein are useful for determining whether a subject has a deletion or duplication syndrome associated with developmental delay, for example one or more of the disorders set forth in Table A and/or Table B. In one embodiment of this aspect, the method comprises selecting the subject for treatment of the deletion or duplication syndrome, for example treatment of a clinical manifestation of the deletion or duplication syndrome. In one embodiment, the method comprises detecting in a genetic sample from the subject the presence of at least one copy number variant (CNV) associated with the deletion or duplication syndrome, analyzing the size of the deletion or duplication, and determining that the patient has the deletion or duplication syndrome if the size of the deletion or duplication is at least about 500 bp, at least about 1,000 bp, at least about 10,000 bp, at least about 100,000 bp, at least about 1 mega base pairs (Mb), at least about 5 Mb, at least about 10 Mb, at least about 15 Mb, at least about 20 Mb, or at least about 50 Mb. CNVs and their respective size are detected by nucleic acid hybridization assays with primers (oligonucleotides) that specifically hybridize to the chromosomal DNA of interest, as explained below (see, e.g., the sequence listing for probes amenable for use with the present invention).

Similarly, the subject is identified as at risk for a clinical manifestation of the deletion or duplication syndrome (and accordingly, selected for treatment for the deletion or duplication syndrome) if the size of the deletion or duplication is at least about 500 bp, at least about 1,000 bp, at least about 10,000 bp, at least about 100,000 bp, at least about 1 mega base pairs (Mb), at least about 5 Mb, at least about 10 Mb, at least about 15 Mb, at least about 20 Mb, or at least about 50 Mb. In another embodiment, the subject is identified as at risk for a clinical manifestation of the deletion or duplication syndrome (and accordingly, selected for treatment for the deletion or duplication syndrome) if the size of the deletion or duplication is about 500 bp to about 20 Mb, or about 500 bp to about 10 Mb, or about 500 bp to about 5 Mb, or about 500 bp to about 1 Mb, or about 500 bp to about 500,000 bp, or about 500 bp to about 100,000 bp, or about 500 bp to about 50,000 bp.

Determination of the presence or absence of the deletion or duplication syndrome, and accordingly, selection for treatment of the deletion or duplication syndrome is dependent upon where the at least one CNV occurs in the genome. Tables A and B provide various deletion and duplication syndromes and corresponding chromosomal regions where CNVs are known to occur in patients having the respective disorder. Therefore, the CNV location can be mapped to a disorder for diagnosis and further identification of the patient for treatment of the disorder (i.e., selection of the patient for treatment).

Besides the syndromes set forth in Tables A and B, exemplary deletion syndromes that can be diagnosed with the methods and compositions provided herein include but are not limited to, for example, Wolf-Hirschhorn (4p) syndrome (WHS), 22q11.2 deletion syndrome (DiGeorge syndrome), and 1p36 deletion syndrome. Exemplary duplication syndromes include, for example, 1q21.1 duplication syndrome or chromosome 15q duplication syndrome. Exemplary clinical manifestations of such disorders include, for example, congenital heart disease, seizure, renal disease, intellectual disability, developmental delay, vision loss, blindness, or other condition affecting ears, skin, teeth, or skeletal development; or a combination thereof. Once a deletion or duplication CNV is identified in a respective subject, the patient in one embodiment is selected for treatment of one or more of the clinical manifestations provided above.

One clinical manifestation that a patient, for example a WHS patient, can be selected for treatment for, is status epilepticus. Accordingly, in one embodiment, the present invention provides a method for selecting a subject for treatment of status epilepticus. Status epilepticus is a life-threatening seizure disorder in which seizures are persistently present in the brain. In one embodiment, the subject in need of treatment for status epilepticus has an additional deletion or duplication syndrome. In one embodiment, the method comprises detecting in a genetic sample from the subject the presence of a CNV associated with a deletion or duplication syndrome. In a further embodiment, the method further comprises detecting in the genetic sample a second CNV provided in Table 3 or Table 4. The present invention also provides a method for selecting a patient for therapy with a glutamatergic or GABAergic drug. Such drugs are known in the art and include glutamate receptor or GABA agonists, antagonists, or allosteric modulators.

In one embodiment, the methods of the present invention comprise detecting in a genetic sample from a subject the presence of at least one CNV. In a further embodiment, the methods provided herein comprise detecting in the genetic sample from the subject the presence of 2, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80, 90, 100, 150, 200, or more CNVs. In another embodiment, the methods comprise detecting in the genetic sample from the subject the presence of from 1 to 100, from 2 to 75, from 5 to 50, or from 10 to 25 CNVs. In one embodiment, the methods provided herein comprise selecting a subject for treatment with a therapy or for treatment for a particular disease, disorder, or condition if the presence of at least 2, at least 5, at least 10, at least 25, or at least 50 CNVs are detected. In some embodiments, the least one CNV is detected using one or more sets of oligonucleotides. In one embodiment, the one or more sets of oligonucleotides are present on an array, such as a high density microarray.

As used herein, the term “ICD-9” refers to the International Classification of Diseases, 9^(th) Revision. This set of classifications is available on the Centers for Disease Control and Prevention website and provides a standardized format for reporting disease classification and mortality statistics.

As used herein, the term “subject” refers to a vertebrate, for example, a mammal. Thus, the subject can be a human. The term does not denote a particular age or sex. Thus, adult and newborn subjects, as well as fetuses, whether male or female, are intended to be covered. Unless otherwise specified, the term “patient” includes human and veterinary subjects.

A “copy number variant” (CNV) includes copy number duplications and deletions, and encompasses a copy number change involving a DNA fragment that is about 500 bp or larger (see e.g., Feuk, et al., 2006 Nature Reviews Genetics, 7, 85-97, incorporated by reference in its entirety herein for all purposes). CNVs described herein do not include those variants that arise from the insertion/deletion of transposable elements (e.g., .about.6-kb Kpnl repeats) to minimize the complexity of CNV analyses. The term CNV therefore encompasses previously introduced terms such as large-scale copy number variants (LCVs; lafrate et al. 2004 Nat Genet. 36:949-951, incorporated by reference in its entirety herein for all purposes), copy number polymorphisms (CNPs; Sebat et al. 2004 Science. 305:525-528, incorporated by reference in its entirety herein for all purposes), and intermediate-sized variants (ISVs; Tuzun et al. 2005 Nat Genet. 37:727-732, incorporated by reference in its entirety herein for all purposes), but not retroposon insertions.

With respect to single stranded nucleic acids, particularly oligonucleotides, the term “specifically hybridize” refers to the association between two single-stranded nucleotide molecules of sufficient complementary sequence to permit such hybridization under pre-determined conditions generally used in the art. In particular, in one embodiment the term refers to hybridization of an oligonucleotide with a substantially complementary sequence contained within a single-stranded DNA or RNA molecule, to the substantial exclusion of hybridization of the oligonucleotide with single-stranded nucleic acids of non-complementary sequence. For example, specific hybridization can refer to a sequence which hybridizes to a first chromosomal region but does not specifically hybridize to a second chromosomal region. Appropriate conditions enabling specific hybridization of single stranded nucleic acid molecules of varying complementarity are well known in the art.

A CNV genetic marker refers to a genomic DNA sequence having a copy number variation, with a known location on a chromosome, which can be used to diagnose subjects with a duplication or deletion syndrome, for example a duplication or deletion syndrome associated with developmental delay and/or to select a subject for treatment of such a syndrome.

The CNV genetic markers associated with ASD described herein, were identified in an extensive replication/refinement study of CNV markers. In particular, a custom array was designed and used to genotype about 3000 individuals with autism and 6000 individuals with normal development. A combination of 2 different statistical and bioinformatics algorithms was used to make the CNV calls and proved to be highly accurate. In particular, 97% of the CNVs called using the combination of algorithms were subsequently validated by other laboratory methods, as compared to 30% using only the individual algorithms (see Example 1). The CNV genetic markers associated with ASD identified herein are provided in Tables 3 and 4. The CNV genetic markers shown in Tables 3 and 4 are those CNV genetic markers having an odds ratio (the likelihood that a given genetic marker is relevant to a diagnosis of ASD in an individual) of 2 or higher.

While certain of the CNV genetic markers associated with developmental delay shown in Table 4 overlap with previously identified CNV genetic markers, the CNVs had not been previously extensively refined and validated until the present study. Therefore, the present invention provides newly identified CNV genetic markers as well as refined and validated genetic markers, that greatly improve the diagnostic yield of developmental delay diagnostic tests over what was previously known. Thus, the present disclosure provides a more diagnostically comprehensive and accurate set of CNV genetic markers associated with developmental delay that can be used in the diagnosis of deletion and/or duplication syndromes associated with developmental delay. Illustrative DNA probes that can be used to genotype individuals for the presence of CNVs associated with developmental delay syndromes, e.g., ASD, are provided in the sequence listing which includes SEQ ID NOs:1-83,433. These DNA probes also include custom probes to genotype other childhood developmental delay disorders, including for example, Rett syndrome, Noonan/Costello/CFC syndromes, Tuberous sclerosis, ADHD, DD, and Tourette syndrome. Illustrative DNA probes for detecting the presence of CNVs associated with developmental delay are provided in SEQ ID NOs: 7410-7426; 12508-12563; 27988-28001; 31283-31314; 32494-32587; 33402-39860; 51803-52100; 61165-61290; 62966-62998; 64149-64167; 69319-69561.

The CNV genetic markers associated with the diagnosis of deletion and/or duplication syndromes associated with developmental delay as described herein are generally defined by their chromosomal location and are referred to by the most recent human genome coordinates (e.g., hg19 chromosomal location coordinates). However, as would be understood by the skilled artisan, as the exact region of the CNV (e.g., the region of highest significance) is further characterized and refined, the CNV region boundaries may shift to the left or to the right while getting smaller, or may get smaller within the same region as originally defined. For example, the CNVs listed in Table 3 are referred to by the CNV region as defined in the discovery cohort as well as the CNV region as defined in the replication cohort. As shown in Table 3, the CNV region for the first listed marker has been reduced from the region spanning chr1:145714421-146101228 to the region spanning chr1: 145703115-145736438, with the left boundary shifting further to the left. The region boundaries for CNV marker number 6 listed in Table 3 have shifted to the right and have been reduced. Therefore, as would be understood by the skilled person, the CNV markers associated with ASD as described herein comprise the CNV region as described herein and include the surrounding region to the left and to the right of the CNV chromosomal region as described herein. Thus, in certain embodiments, the chromosomal region encompassing the CNV genetic markers associated with one of the duplication or deletion syndromes described herein may comprise the chromosomal region 50, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 6000, 7000, 8000, 9000, 10000, 15,000, 20000, 30000, 40000, 50,000, 60,000, 70,000, 80,000, 90,000, 100,000, or more positions to the left and/or to the right of the chromosomal region as described herein.

In one embodiment, reagents for detecting the CNV genetic markers as described herein include reagents which specifically hybridize to the chromosomal regions surrounding the region specifically described herein. In particular, a nucleic acid reagent for detecting the CNV genetic markers as described herein may specifically hybridize to the chromosomal region 50, 900, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 6000, 7000, 8000, 9000, 10000, 15,000, 20000, 30000, 40000, 50,000, 60,000, 70,000, 80,000, 90,000, 100,000, or more positions to the left and/or to the right of the chromosomal region of the CNV genetic marker as described herein.

In embodiments where methods are provided for diagnosis of subjects with a deletion or duplication syndrome associated with mitochondrial function, the CNV that is probed for is a copy number variant of one or more of the genes set forth in Table 18, i.e., a gene associated with mitochondrial function. For example, in one embodiment, the CNV is a CNV that affects one or more, two or more, five or more or ten or more of the mitochondrial associated genes set forth in Table 15. In another embodiment, the at least one CNV is a CNV that affects one to ten, one to nine, one to eight or one to five of the mitochondrial associated genes set forth in Table 18.

In one embodiment, the presence of one or more CNVs described herein indicates that an individual is affected with the deletion or duplication syndrome, or is predisposed to developing the deletion or duplication syndrome. In another embodiment, the presence of one or more CNV genetic markers described herein may be predictive of whether an individual is at risk for or susceptible to the deletion or duplication syndrome. If certain genetic polymorphisms (e.g., CNVs) are detected more frequently in people with the deletion or duplication syndrome, the variations are said to be “associated” with the particular deletion or duplication syndrome. In this regard, variations may be associated with any of the deletion or duplication syndromes set forth herein, for example the deletion or duplication syndromes set forth in Table A and Table B. The polymorphisms associated with ASD may either directly cause the disease phenotype or they may be in linkage disequilibrium (LD) with nearby genetic mutations that influence the individual variation in the disease phenotype. As used herein, LD is the nonrandom association of alleles at 2 or more loci.

In each of the methods described herein, the presence or absence of one or more CNVs (e.g., one or more, two or more, five or more, ten or more CNVs) is probed for in a sample obtained from a subject. “Sample” or “biological sample,” as used herein, refers to a sample obtained from a human subject or a patient, which may be tested for a particular molecule, for example one or more of the CNVs associated with a deletion or duplication syndrome, as set forth herein. Samples may include but are not limited to cells, buccal swab sample, body fluids, including blood, serum, plasma, urine, saliva, cerebral spinal fluid, tears, pleural fluid and the like. Samples that are suitable for use in the methods described herein contain genetic material, e.g., genomic DNA (gDNA). Non-limiting examples of sources of samples include urine, blood, and tissue. The sample itself will typically consist of nucleated cells (e.g., blood or buccal cells), tissue, etc., removed from the subject. The subject can be an adult, child, fetus, or embryo. In some embodiments, the sample is obtained prenatally, either from a fetus or embryo or from the mother (e.g., from fetal or embryonic cells in the maternal circulation). Methods and reagents are known in the art for obtaining, processing, and analyzing samples. In some embodiments, the sample is obtained with the assistance of a health care provider, e.g., to draw blood. In some embodiments, the sample is obtained without the assistance of a health care provider, e.g., where the sample is obtained non-invasively, such as a sample comprising buccal cells that is obtained using a buccal swab or brush, or a mouthwash sample.

Cells can be harvested from a biological sample using standard techniques known in the art. For example, cells can be harvested by centrifuging a cell sample and resuspending the pelleted cells. The cells can be resuspended in a buffered solution such as phosphate-buffered saline (PBS). After centrifuging the cell suspension to obtain a cell pellet, the cells can be lysed to extract DNA, e.g., genomic DNA. All samples obtained from a subject, including those subjected to any sort of further processing, are considered to be obtained from the subject.

The sample in one embodiment, is further processed before the detection of the presence or absence of the one or more CNVs. For example, DNA, e.g., genomic DNA in a cell or tissue sample can be separated from other components of the sample. The sample can be concentrated and/or purified to isolate genomic DNA in a non-natural state. Specifically, genomic DNA exists as genomic chromosomal DNA and is a tightly coiled structure, wherein the DNA is coiled many times around histone proteins that support the genomic DNA and chromosomal structure. In the methods provided herein, the higher order structure of the genomic DNA (e.g., tertiary and quaternary structures) is modified considerably by eliminating histone proteins from the sample, and digesting the genomic DNA into fragments with frequent cutting restriction endonucleases. Genomic DNA therefore does not exist as natural genomic DNA, it is present in small fragments (with lengths ranging from about 100 basepairs to about 500 basepairs) rather than as large polymers on individual chromosomes, comprising tens to hundreds of megabase pairs.

Once the genomic DNA is digested and chemically modified into a non-natural sequence and structure, it is amplified, in one embodiment, with primers that introduce an additional DNA sequence (adapter sequence) onto the fragments (with the use of adapter-specific primers). Amplification therefore serves to create non-natural double stranded molecules, by introducing adapter sequences into the already non-natural restriction digested, and chemically modified genomic DNA. Further, as known to those of ordinary skill in the art, amplification procedures have error rates associated with them. Therefore, amplification introduces further modifications into the smaller DNA fragments. In one embodiment, during amplification with the adapter-specific primers, a detectable label, e.g., a fluorophore, is added to single strand DNA fragments. Amplification therefore also serves to create DNA complexes that do not occur in nature, at least because of (i) the addition of adapter sequences, (ii) the error rate associated with amplification, (iii) the disparate structure of these complexes as compared to what exists in nature, i.e., large polymers of DNA wrapped around histone proteins and the chemical addition of a detectable label to the DNA fragments.

Once a sample is obtained, it is interrogated for one or more of the CNVs set forth herein.

In general, the one or more CNVs can be identified using a nucleic acid hybridization assay alone or in combination with an amplification assay, i.e., to amplify the nucleic acid in the sample prior to detection. In one embodiment, the genomic DNA of the sample is sequenced or hybridized to an array, as described in detail herein. A determination is then made as to whether the sample includes the one or more CNVs depending on the detected hybridization pattern, or rather, includes the “normal” or “wild type” sequence (also referred to as a “reference sequence” or “reference allele”).

Detection using a hybridization assay comprises the generation of non-natural DNA complexes, that is, DNA complexes that do not exist in nature. As mentioned above, the DNA that is used in the hybridization assay is already in a non-natural state because of various modifications, specifically, (i) modifications to the length of the DNA, (ii) modifications to the primary structure of the DNA via the addition of adapter sequences during the amplification process, (iii) modifications to the higher order structure of the DNA due to the elimination of histone proteins and other cellular material, (iv) chemical modifications due to the addition of a detectable label to the digested DNA fragments, and (v) further chemical modifications due to introduction of bases that do not occur in the native chromosomal DNA, due to inherent error in the amplification reaction (leading to further change in primary structure as compared to chromosomal genomic DNA).

In the case of a hybridization assay, for example a microarray assay or bead based assay, hybridization occurs between the non-natural fragments described above and an immobilized sequence of known identity. Therefore, the product of the hybridization assay is further removed from DNA duplexes that exist in nature, because of the reasons set forth above, and because each is immobilized, for example to a glass slide or bead.

In one embodiment, if the hybridization assay reveals a difference between the sequenced region and the reference sequence (which can be included in the hybridization assay as a control, or in a dataset, for example, a statistical training set), a CNV has been identified. Certain statistical algorithms can aid in this determination, as described herein. The fact that a difference in nucleotide sequence is identified at a particular site that determines that a CNV exists at that site.

For example, an oligonucleotide or oligonucleotide pair can be used in the methods described herein, for example in a microarray or polymerase chain reaction assay, to detect the one or more CNVs.

The term “oligonucleotide” refers to a relatively short polynucleotide (e.g., 100, 50, 20 or fewer nucleotides) including, without limitation, single-stranded deoxyribonucleotides, single- or double-stranded ribonucleotides, RNA:DNA hybrids and double-stranded DNAs. Oligonucleotides, such as single-stranded DNA probe oligonucleotides, are often synthesized by chemical methods, for example using automated oligonucleotide synthesizers that are commercially available. However, oligonucleotides can be made by a variety of other methods, including in vitro recombinant DNA-mediated techniques and by expression of DNAs in cells and organisms. Oligonucleotides for use in detecting the presence or absence of certain CNVs associated with chromosomal deletion or duplication syndromes are provided in the accompanying sequence listing.

In the context of the present invention, an “isolated” or “purified” nucleic acid molecule, e.g., a DNA molecule or RNA molecule, is a DNA molecule or RNA molecule that exists apart from its native environment and is therefore not a product of nature. An isolated DNA molecule or RNA molecule may exist in a purified form or may exist in a non-native environment such as, for example, a transgenic host cell. For example, an “isolated” or “purified” nucleic acid molecule is substantially free of other cellular material or culture medium when produced by recombinant techniques, or substantially free of chemical precursors or other chemicals when chemically synthesized. In one embodiment, an “isolated” nucleic acid is free of sequences that naturally flank the nucleic acid (i.e., sequences located at the 5′ and 3′ ends of the nucleic acid) in the genomic DNA of the organism from which the nucleic acid is derived. In another embodiment, the “isolated nucleic acid” comprises a DNA molecule inserted into a vector, such as a plasmid or virus vector, or integrated into the genomic DNA of a prokaryote or eukaryote. An “isolated nucleic acid molecule” may also comprise a cDNA molecule or an oligonucleotide primer or probe, or additional sequences added onto a fragment of DNA, for example, an adapter sequence added to a restriction cut portion of genomic DNA.

As used herein a set of oligonucleotides, in one embodiment, comprises from about 2 to about 100 oligonucleotides, all of which specifically hybridize to a particular CNV or region thereof, which includes for example one of the chromosomal regions set forth in Table A or Table B, or one or more of the CNVs set forth herein. In one embodiment, a set of oligonucleotides comprises from about 5 to about 100 oligonucleotides (or from about 5 to about 30 oligonucleotide pairs), from about 10 to about 100 oligonucleotides (or from about 10 to about 100 oligonucleotide pairs), from about 10 to about 75 oligonucleotides (or from about 10 to about 75 oligonucleotide pairs), from about 10 to about 50 oligonucleotides (or from about 10 to about 0 oligonucleotide pairs). In one embodiment, a set of oliognucleotides comprises about 15 to about 50 oligonucleotides, all of which specifically hybridize to a particular CNV associated with a deletion or duplication syndrome, for example, a deletion or duplication syndrome associated with developmental delay. In one embodiment, a set of oligonucleotides comprises DNA probes, e.g., genomic DNA probes. In one embodiment, the DNA probes comprise DNA probes that overlap in genomic sequence. In another embodiment, the DNA probes comprise DNA probes that do not overlap in genomic sequence. In one embodiment, the DNA probes provide detection coverage over the length of a CNV associated with a deletion or duplication syndrome, for example, a deletion or duplication syndrome associated with developmental delay. In another embodiment, a set of oligonucleotides comprises amplification primers that amplify a CNV or region thereof, wherein the CNV is associated with a deletion or duplication syndrome, for example, a deletion or duplication syndrome associated with developmental delay. In this regard, sets of oligonucleotides comprising amplification primers may comprise multiplex amplification primers. In another embodiment, the sets of oligonucleotides or DNA probes may be provided on an array, such as solid phase arrays, chromosomal/DNA microarrays, or micro-bead arrays.

Illustrative reagents for detecting genetic markers include nucleic acids, and in particular include oligonucleotides. A nucleic acid can be DNA or RNA, and may be single or double stranded. In one embodiment, the oligonucleotides are DNA probes, or primers for amplifying nucleic acids of genetic markers. In one embodiment, the oligonucleotides of the present invention are capable of specifically hybridizing (e.g, under stringent hybridization conditions), with complementary regions of a genetic marker associated with ASD containing a genetic polymorphism described herein, such as a dopy number variation. Oligonucleotides can be naturally occurring or synthetic, but are typically prepared by synthetic means. Oligonucleotides, as described herein, may include segments of DNA, or their complements. The exact size of the oligonucleotide will depend on various factors and on the particular application and use of the oligonucleotide. Oligonucleotides, which include probes and primers, can be any length from 3 nucleotides to the full length of a target nucleic acid molecule of interest (e.g., a nucleic acid molecule of a CNV genetic marker associated with a deletion or duplication syndrome set forth herein, such as those provided in Tables A and B), and explicitly include every possible number of contiguous nucleic acids from 3 through the full length of a target polynucleotide of interest. Thus, oligonucleotides can be between 5 and 100 contiguous bases, and often range from 5, 10, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, or 25 nucleotides to 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 100 nucleotides. Oligonucleotides between 5-10, 5-20, 10-20, 12-30, 15-30, 10-50, 20-50 or 20-100 bases in length are common.

Oligonucleotides of the present invention can be RNA, DNA, or derivatives of either. The minimum size of such oligonucleotides is the size required for formation of a stable hybrid between an oligonucleotide and a complementary sequence on a nucleic acid molecule of the present invention (i.e., the copy number variant genetic markers described herein). The present invention includes oligonucleotides that can be used as, for example, probes to identify nucleic acid molecules (e.g., DNA probes) or primers to amplify nucleic acid molecules.

In one embodiment, an oligonucleotide may be a probe which refers to an oligonucleotide, polynucleotide or nucleic acid, either RNA or DNA, whether occurring naturally as in a purified restriction enzyme digest or produced synthetically, which is capable of annealing with or specifically hybridizing to a nucleic acid with sequences complementary to the probe. A probe may be either single-stranded or double-stranded. The exact length of the probe will depend upon many factors, including temperature, source of probe and use of the method. For example, for diagnostic applications, depending on the complexity of the target sequence, the oligonucleotide probe typically contains 15-25 or more nucleotides, although it may contain fewer nucleotides. In certain embodiments, a probe can be between 5 and 100 contiguous bases, and is generally about 5, 10, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, or 25 nucleotides in length, or may be about 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 100 nucleotides in length. The probes herein are selected to be complementary to different strands of a particular target nucleic acid sequence. This means that the probes must be sufficiently complementary so as to be able to specifically hybridize or anneal with their respective target strands under a set of pre-determined conditions. Therefore, the probe sequence need not reflect the exact complementary sequence of the target. For example, a non-complementary nucleotide fragment may be attached to the 5′ or 3′ end of the probe, with the remainder of the probe sequence being complementary to the target strand. Alternatively, non-complementary bases or longer sequences can be interspersed into the probe, provided that the probe sequence has sufficient complementarity with the sequence of the target nucleic acid to anneal therewith specifically. Illustrative probes for detecting the genetic markers associated with ASD and other childhood developmental delay disorders are set forth in SEQ ID NOs:1-83,443. In particular, DNA probes for detecting CNVs associated with ASD are set forth in SEQ ID NOs: 7410-7426; 12508-12563; 27988-28001; 31283-31314; 32494-32587; 33402-39860; 51803-52100; 61165-61290; 62966-62998; 64149-64167; 69319-69561. (See also Table 11 for a description of the childhood developmental delay disorders and the custom DNA probes provided in the sequence listing and Table 14 from U.S. Provisional Application 61/977,462 and Table 14 from International PCT Publication No. 2014/055915, the disclosure of each of which is incorporated by reference in their entireties). As would be recognized by the skilled person, a specific probe or probe set disclosed herein for detecting a particular CNV associated with ASD (or other disorder), can be identified by using the hg19 chromosomal location start and end coordinates of a CNV of interest (e.g., a CNV listed in Table 3 or 4) to query Table 14 from the aforementioned references, to find a corresponding overlapping chromosomal location

In one embodiment, an oligonucleotide may be a primer, which refers to an oligonucleotide, either RNA or DNA, either single-stranded or double-stranded, either derived from a biological system, generated by restriction enzyme digestion, or produced synthetically which, when placed in the proper environment, is able to functionally act as an initiator of template-dependent nucleic acid synthesis. When presented with an appropriate nucleic acid template, suitable nucleoside triphosphate precursors of nucleic acids, a polymerase enzyme, suitable cofactors and conditions such as a suitable temperature and pH, the primer may be extended at its 3′ terminus by the addition of nucleotides by the action of a polymerase or similar activity to yield a primer extension product. The primer may vary in length depending on the particular conditions and requirement of the application. For example, in certain applications, an oligonucleotide primer is about 15-25 or more nucleotides in length, but may in certain embodiments be between 5 and 100 contiguous bases, and often be about 5, 10, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, or 25 nucleotides long or, in certain embodiments, may be about 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 100 nucleotides in length for. The primer must be of sufficient complementarity to the desired template to prime the synthesis of the desired extension product, that is, to be able to anneal with the desired template strand in a manner sufficient to provide the 3′ hydroxyl moiety of the primer in appropriate juxtaposition for use in the initiation of synthesis by a polymerase or similar enzyme. It is not required that the primer sequence represent an exact complement of the desired template. For example, a non-complementary nucleotide sequence may be attached to the 5′ end of an otherwise complementary primer. Alternatively, non-complementary bases may be interspersed within the oligonucleotide primer sequence, provided that the primer sequence has sufficient complementarity with the sequence of the desired template strand to functionally provide a template-primer complex for the synthesis of the extension product.

In one embodiment, detection of one or more CN Vs comprises the use of one or more DNA probes or sets of probes as set forth in SEQ ID NOs:1-83,443. In one embodiment, an array comprises at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, or more DNA probes as set forth in SEQ ID NOs:1-83,443. In another embodiment, an array for identifying the genotype of a subject suspected of having ASD or other childhood developmental delay disorder, comprises at least about 25-2500, or at least 100, 1000, 10000, 15000, 16000, 17000, 18000, 19000, 20000, 25000, 30000, 35000, 40000, 45000, 50000, 55000, 60000, 65000 or more of the DNA probes forth in SEQ ID NOs:1-83,443. In another embodiment, an array for genotyping an individual for the presence of a CNV associated with ASD or other childhood developmental delay disorder, comprises the DNA probes set forth in the sequence listing and identified in Table 14 from U.S. Provisional Application 61/977,462 and Table 14 from International PCT Publication No. 2014/055915, the disclosure of each of which is incorporated by reference in their entireties that are custom probes for the CNVs listed in Tables 8 and 9, which specifically hybridize to the CNVs identified in Table 3 and 4. In one embodiment, an array for genotyping an individual for the presence of a CNV associated with ASD, comprises the DNA probes set forth in SEQ ID NOs: 7410-7426; 12508-12563; 27988-28001; 31283-31314; 32494-32587; 33402-39860; 51803-52100; 61165-61290; 62966-62998; 64149-64167; 69319-69561.

In one embodiment, hybridization on a microarray is used to detect the presence of one or more SNPs in a patient's sample. The term “microarray” refers to an ordered arrangement of hybridizable array elements, e.g., polynucleotide probes, on a substrate.

In another embodiment of the invention, constant denaturant capillary electrophoresis (CDCE) can be combined with high-fidelity PCR (HiFi-PCR) to detect the presence of one or more CNVs. In another embodiment, high-fidelity PCR is used. In yet another embodiment, denaturing HPLC, denaturing capillary electrophoresis, cycling temperature capillary electrophoresis, allele-specific PCRs, quantitative real time PCR approaches such as TaqMan® is employed to detect the one or more CNVs. Other approaches to detect the presence of one or more CNVs, and in some cases, the size (i.e., as reported in bases or base pairs) of the one or more CNVs, amenable for use with the present invention include polony sequencing approaches, microarray approaches, mass spectrometry, high-throughput sequencing approaches, e.g., at a single molecule level, and the NanoString approach.

Hybridization detection methods are based on the formation of specific hybrids between complementary nucleic acid sequences that serve to detect nucleic acid sequence mutation(s) and are amenable for use with the methods described herein. Methods of nucleic acid analysis to detect polymorphisms and/or polymorphic variants (copy number variants) include, e.g., microarray analysis and real time PCR. Hybridization methods, such as Southern analysis, Northern analysis, or in situ hybridizations, can also be used (see Current Protocols in Molecular Biology, Ausubel et al., eds., John Wiley & Sons 2003, incorporated by reference in its entirety).

Other methods for use with the methods provided herein include direct manual sequencing (Church and Gilbert, Proc. Natl. Acad. Sci. USA 81:1991-1995 (1988); Sanger et al., Proc. Natl. Acad. Sci. USA 74:5463-5467 (1977); Beavis et al. U.S. Pat. No. 5,288,644, each incorporated by reference in its entirety for all purposes); automated fluorescent sequencing; single-stranded conformation polymorphism assays (SSCP); clamped denaturing gel electrophoresis (CDGE); two-dimensional gel electrophoresis (2DGE or TDGE); conformational sensitive gel electrophoresis (CSGE); denaturing gradient gel electrophoresis (DGGE) (Sheffield et al., Proc. Natl. Acad. Sci. USA 86:232-236 (1989)), mobility shift analysis (Orita et al., Proc. Natl. Acad. Sci. USA 86:2766-2770 (1989), incorporated by reference in its entirety), restriction enzyme analysis (Flavell et al., Cell 15:25 (1978); Geever et al., Proc. Natl. Acad. Sci. USA 78:5081 (1981), incorporated by reference in its entirety); quantitative real-time PCR (Raca et al., Genet Test 8(4):387-94 (2004), incorporated by reference in its entirety); heteroduplex analysis; chemical mismatch cleavage (CMC) (Cotton et al., Proc. Natl. Acad. Sci. USA 85:4397-4401 (1985), incorporated by reference in its entirety); RNase protection assays (Myers et al., Science 230:1242 (1985), incorporated by reference in its entirety); use of polypeptides that recognize nucleotide mismatches, e.g., E. coli mutS protein; allele-specific PCR, for example. See, e.g., U.S. Patent Publication No. 2004/0014095, which is incorporated herein by reference in its entirety.

In order to detect the CNV(s) described herein, in one embodiment, genomic DNA (gDNA) or a portion thereof containing the polymorphic site, present in the sample obtained from the subject, is first amplified. Such regions can be amplified and isolated by PCR using oligonucleotide primers designed based on genomic and/or cDNA sequences that flank the site. See e.g., PCR Primer: A Laboratory Manual, Dieffenbach and Dveksler, (Eds.); McPherson et al., PCR Basics: From Background to Bench (Springer Verlag, 2000, incorporated by reference in its entirety); Mattila et al., Nucleic Acids Res., 19:4967 (1991), incorporated by reference in its entirety; Eckert et al., PCR Methods and Applications, 1:17 (1991), incorporated by reference in its entirety; PCR (eds. McPherson et al., IRL Press, Oxford), incorporated by reference in its entirety; and U.S. Pat. No. 4,683,202, incorporated by reference in its entirety. Other amplification methods that may be employed include the ligase chain reaction (LCR) (Wu and Wallace, Genomics, 4:560 (1989), Landegren et al., Science, 241:1077 (1988), transcription amplification (Kwoh et al., Proc. Natl. Acad. Sci. USA, 86:1173 (1989)), self-sustained sequence replication (Guatelli et al., Proc. Natl. Acad. Sci. USA, 87:1874 (1990)), incorporated by reference in its entirety, and nucleic acid based sequence amplification (NASBA). Guidelines for selecting primers for PCR amplification are known to those of ordinary skill in the art. See, e.g., McPherson et al., PCR Basics: From Background to Bench, Springer-Verlag, 2000, incorporated by reference in its entirety. A variety of computer programs for designing primers are available.

In one example, a sample (e.g., a sample comprising genomic DNA), is obtained from a subject. The DNA in the sample is then examined to determine a CNV profile as described herein. The profile is determined by any method described herein, e.g., by sequencing or by hybridization of genomic DNA, RNA, or cDNA to a nucleic acid probe, e.g., a DNA probe (which includes cDNA and oligonucleotide probes) or an RNA probe. The nucleic acid probe can be designed to specifically or preferentially hybridize with a particular polymorphic variant.

In certain embodiments, the oligonucleotides for detecting CNV genetic markers associated with the duplication and deletion syndromes set forth herein may be used in high throughput sequencing methods (often referred to as next-generation sequencing methods or next-gen sequencing methods). Accordingly, in one embodiment, the present disclosure provides methods of determing or predicting the presence or absence of a deletion or duplication syndrome by detecting in a genetic sample from the subject one or more CNVs by high throughput sequencing. High throughput sequencing, or next-generation sequencing, methods are known in the art (see, e.g., Zhang et al., J Genet Genomics. 2011 Mar. 20; 38(3):95-109; Metzker, Nat Rev Genet. 2010 January; 11(1):31-46, incorporated by reference herein in its entirety) and include, but are not limited to, technologies such as ABI SOLiD sequencing technology (now owned by Life Technologies, Carlsbad, Calif.); Roche 454 FLX which uses sequencing by synthesis technology known as pyrosequencing (Roche, Basel Switzerland); IIlumina Genome Analyzer (Illumina, San Diego, Calif.); Dover Systems Polonator G.007 (Salem, N.H.); Helicos (Helicos BioSciences Corporation, Cambridge Mass., USA), and Sanger. In one embodiment, DNA sequencing may be performed using methods well known in the art including mass spectrometry technology and whole genome sequencing technologies (e.g., those used by Pacific Biosciences, Menlo Park, Calif., USA), etc.

In one embodiment, nucleic acid, for example, genomic DNA is sequenced using nanopore sequencing, to determine the presence of the one or more CNVs (e.g., as described in Soni et al. (2007). Clin Chem 53, pp. 1996-2001, incorporated by reference in its entirety for all purposes). Nanopore sequencing is a single-molecule sequencing technology whereby a single molecule of DNA is sequenced directly as it passes through a nanopore. A nanopore has a diameter on the order of 1 nanometer. Immersion of a nanopore in a conducting fluid and application of a potential (voltage) across it results in a slight electrical current due to conduction of ions through the nanopore. The amount of current which flows is sensitive to the size and shape of the nanopore. As a DNA molecule passes through a nanopore, each nucleotide on the DNA molecule obstructs the nanopore to a different degree, changing the magnitude of the current through the nanopore in different degrees. Thus, this change in the current as the DNA molecule passes through the nanopore represents a reading of the DNA sequence. Nanopore sequencing technology as disclosed in U.S. Pat. Nos. 5,795,782, 6,015,714, 6,627,067, 7,238,485 and 7,258,838 and U.S. patent application publications U.S. Patent Application Publication Nos. 2006/003171 and 2009/0029477, each incorporated by reference in its entirety for all purposes, is amenable for use with the methods described herein

Nucleic acid probes can be used to detect and/or quantify the presence of a particular target nucleic acid sequence within a sample of nucleic acid sequences, e.g., as hybridization probes, or to amplify a particular target sequence within a sample, e.g., as a primer. Probes have a complimentary nucleic acid sequence that selectively hybridizes to the target nucleic acid sequence. In order for a probe to hybridize to a target sequence, the hybridization probe must have sufficient identity with the target sequence, i.e., at least 70%, e.g., 80%, 90%, 95%, 98% or more identity to the target sequence. The probe sequence must also be sufficiently long so that the probe exhibits selectivity for the target sequence over non-target sequences. For example, the probe will be at least 10, e.g., 15, 20, 25, 30, 35, 50, 100, or more, nucleotides in length. In some embodiments, the probes are not more than 30, 50, 100, 200, 300, or 500 nucleotides in length. Probes include primers, which generally refers to a single-stranded oligonucleotide probe that can act as a point of initiation of template-directed DNA synthesis using methods such as PCR (polymerase chain reaction), LCR (ligase chain reaction), etc., for amplification of a target sequence.

Control probes can also be used. For example, a probe that binds a less variable sequence, e.g., repetitive DNA associated with a centromere of a chromosome, or a probe that exhibits differential binding to the polymorphic site being interrogated, can be used as a control. Probes that hybridize with various centromeric DNA and locus-specific DNA are available commercially, for example, from Vysis, Inc. (Downers Grove, Ill.), Molecular Probes, Inc. (Eugene, Oreg.), or from Cytocell (Oxfordshire, UK).

In some embodiments, the probes are labeled with a detectable label, e.g., by direct labeling. In various embodiments, the oligonucleotides for detecting the one or more SNP genetic markers associated with ASD described herein are conjugated to a detectable label that may be detected directly or indirectly. In the present invention, oligonucleotides may all be covalently linked to a detectable label.

In one embodiment, CNV size is determined via a nucleic acid hybridization method as follows. Oligonucleotide probes are employed and each represents a known chromosomal coordinate based on hg19 coordinates. In a subject who has no deletion or duplication in a particular region, all probes specific to that region will have a uniform signal that represents having 2 copies of each chromosome at that position. A CNV is detected by looking for increases (duplication) or decreases (deletion) in signal intensity at individual probes, each of which represent a unique location in the genome. When 25 or more probes targeting contiguous regions of the genome show a reduced signal compared to an individual with no CNV, the test individual can then be said to have a deletion at the location containing the probes that have a reduced signal. Similarly, when 25 or more probes (for example 30 or more probes, or 50 or more probes) targeting contiguous regions of the genome show an increased signal compared to an individual with no CNV, the test individual can then be said to have a duplication at the location containing the probes that have an increased signal. Since the genomic coordinates of each probe are known, CNV size is determined by the coordinates of the probes showing reduced (in the case of a deletion) or increased (in the case of a duplication) signal intensity, and the maximal CNV boundaries are defined by the probes nearest to those showing reduced (deletion) signal or increased (duplication) signal that themselves do not show a reduced (deletion) signal or increased (duplication) signal.

For example, consider an example with oligonucleotide probes each having an arbitrary size of 1 unit for each probe. Probes 1-10 show a normal signal (e.g., as the probe is labeled with a detectable label), probes 11-67 show a reduced signal, and probes 68-1000 show a normal signal again. In this case, there is a deletion that is at least 56 units (67−11=56) in size, and at most 58 units in size (68−10). The CNV boundaries lie somewhere between probes 10 and 11 on the “left” end and between probes 67 and 68 on the “right” end. The same is true for a duplication, but one probes for an increase in signal intensity compared to a subject with no CNV, and duplications must include ≧0.50 probes to be detectable.

Where non-microarray based hybridization methods are employed to detect the presence or absence of a CNV, the size of the CNV can also be determined. For example, in a sequencing embodiment, the number of sequence reads of a particular sequence can be used to make a determination of whether a deletion or duplication occurs at the particular chromosomal location. Specifically, the number of sequence reads at a particular genomic DNA location can be compared to the number of sequence reads measured or that would be expected for a sample that does not include the CNV.

As provided above, an oligonucleotide probe or probes designed to hybridize a CNV or portion thereof can be labeled with a detectable label. A “detectable label” is a molecule or material that can produce a detectable (such as visually, electronically or otherwise) signal that indicates the presence and/or concentration of the label in a sample. When conjugated to a nucleic acid such as a DNA probe, the detectable label can be used to locate and/or quantify a target nucleic acid sequence to which the specific probe is directed. Thereby, the presence and/or amount of the target in a sample can be detected by detecting the signal produced by the detectable label. A detectable label can be detected directly or indirectly, and several different detectable labels conjugated to different probes can be used in combination to detect one or more targets.

Examples of detectable labels, which may be detected directly, include fluorescent dyes and radioactive substances and metal particles. In contrast, indirect detection requires the application of one or more additional probes or antibodies, i.e., secondary antibodies, after application of the primary probe or antibody. Thus, in certain embodiments, as would be understood by the skilled artisan, the detection is performed by the detection of the binding of the secondary probe or binding agent to the primary detectable probe. Examples of primary detectable binding agents or probes requiring addition of a secondary binding agent or antibody include enzymatic detectable binding agents and hapten detectable binding agents or antibodies.

In some embodiments, the detectable label is conjugated to a nucleic acid polymer which comprises the first binding agent (e.g., in an ISH, WISH, or FISH process). In other embodiments, the detectable label is conjugated to an antibody which comprises the first binding agent (e.g., in an IHC process).

Examples of detectable labels which may be conjugated to the oligonucleotides used in the methods of the present disclosure include fluorescent labels, enzyme labels, radioisotopes, chemiluminescent labels, electrochemiluminescent labels, bioluminescent labels, polymers, polymer particles, metal particles, haptens, and dyes.

Examples of fluorescent labels include 5-(and 6)-carboxyfluorescein, 5- or 6-carboxyfluorescein, 6-(fluorescein)-5-(and 6)-carboxamido hexanoic acid, fluorescein isothiocyanate, rhodamine, tetramethylrhodamine, and dyes such as Cy2, Cy3, and Cy5, optionally substituted coumarin including AMCA, PerCP, phycobiliproteins including R-phycoerythrin (RPE) and allophycoerythrin (APC), Texas Red, Princeton Red, green fluorescent protein (GFP) and analogues thereof, and conjugates of R-phycoerythrin or allophycoerythrin, inorganic fluorescent labels such as particles based on semiconductor material like coated CdSe nanocrystallites.

Examples of polymer particle labels include micro particles or latex particles of polystyrene, PMMA or silica, which can be embedded with fluorescent dyes, or polymer micelles or capsules which contain dyes, enzymes or substrates.

Examples of metal particle labels include gold particles and coated gold particles, which can be converted by silver stains. Examples of haptens include DNP, fluorescein isothiocyanate (FITC), biotin, and digoxigenin. Examples of enzymatic labels include horseradish peroxidase (HRP), alkaline phosphatase (ALP or AP), β-galactosidase (GAL), glucose-6-phosphate dehydrogenase, β-N-acetylglucosamimidase, β-glucuronidase, invertase, Xanthine Oxidase, firefly luciferase and glucose oxidase (GO). Examples of commonly used substrates for horseradishperoxidase include 3,3′-diaminobenzidine (DAB), diaminobenzidine with nickel enhancement, 3-amino-9-ethylcarbazole (AEC), Benzidine dihydrochloride (BDHC), Hanker-Yates reagent (HYR), Indophane blue (IB), tetramethylbenzidine (TMB), 4-chloro-1-naphtol (CN), α-naphtol pyronin (α.-NP), o-dianisidine (OD), 5-bromo-4-chloro-3-indolylphosphate (BCIP), Nitro blue tetrazolium (NBT), 2-(p-iodophenyl)-3-p-nitropheny-1-5-phenyl tetrazolium chloride (INT), tetranitro blue tetrazolium (TNBT), 5-bromo-4-chloro-3-indoxyl-beta-D-galactoside/ferro-ferricyanide (BCIG/FF).

Examples of commonly used substrates for Alkaline Phosphatase include Naphthol-AS-B 1-phosphate/fast red TR (NABP/FR), Naphthol-AS-MX-phosphate/fast red TR (NAMP/FR), Naphthol-AS-B1-phosphate/-fast red TR (NABP/FR), Naphthol-AS-MX-phosphate/fast red TR (NAMP/FR), Naphthol-AS-B1-phosphate/new fuschin (NABP/NF), bromochloroindolyl phosphate/nitroblue tetrazolium (BCIP/NBT), 5-Bromo-4-chloro-3-indolyl-b-d-galactopyranoside (BCIG).

Examples of luminescent labels include luminol, isoluminol, acridinium esters, 1,2-dioxetanes and pyridopyridazines. Examples of electrochemiluminescent labels include ruthenium derivatives. Examples of radioactive labels include radioactive isotopes of iodide, cobalt, selenium, tritium, carbon, sulfur and phosphorous.

Detectable labels may be linked to any molecule that specifically binds to a biological marker of interest, e.g., an antibody, a nucleic acid probe, or a polymer. Furthermore, one of ordinary skill in the art would appreciate that detectable labels can also be conjugated to second, and/or third, and/or fourth, and/or fifth binding agents, nucleic acids, or antibodies, etc. Moreover, the skilled artisan would appreciate that each additional binding agent or nucleic acid used to characterize a biological marker of interest (e.g., the CNV genetic markers associated with ASD) may serve as a signal amplification step. The biological marker may be detected visually using, e.g., light microscopy, fluorescent microscopy, electron microscopy where the detectable substance is for example a dye, a colloidal gold particle, a luminescent reagent. Visually detectable substances bound to a biological marker may also be detected using a spectrophotometer. Where the detectable substance is a radioactive isotope detection can be visually by autoradiography, or non-visually using a scintillation counter. See, e.g., Larsson, 1988, Immunocytochemistry: Theory and Practice, (CRC Press, Boca Raton, Fla.); Methods in Molecular Biology, vol. 80 1998, John D. Pound (ed.) (Humana Press, Totowa, N.J.).

In other embodiments, the probes can be indirectly labeled with, e.g., biotin or digoxygenin, or labeled with radioactive isotopes such as ³²P and ³H. For example, a probe indirectly labeled with biotin can be detected by avidin conjugated to a detectable marker. For example, avidin can be conjugated to an enzymatic marker such as alkaline phosphatase or horseradish peroxidase. Enzymatic markers can be detected in standard colorimetric reactions using a substrate and/or a catalyst for the enzyme. Catalysts for alkaline phosphatase include 5-bromo-4-chloro-3-indolylphosphate and nitro blue tetrazolium. Diaminobenzoate can be used as a catalyst for horseradish peroxidase.

Oligonucleotide probes that exhibit differential or selective binding to polymorphic sites may readily be designed by one of ordinary skill in the art. For example, an oligonucleotide that is perfectly complementary to a sequence that encompasses a polymorphic site (i.e., a sequence that includes the polymorphic site, within it or at one end) will generally hybridize preferentially to a nucleic acid comprising that sequence, as opposed to a nucleic acid comprising an alternate polymorphic variant.

In another aspect, the invention features arrays that include a substrate having a plurality of addressable areas, and methods of using them. At least one area of the plurality includes a nucleic acid probe that binds specifically to a sequence comprising a CNV, for example one of the chromosomal locations set forth at Tables A and/or B, or one or more CNVs set forth in one or more of Tables 8-10 and 12-13, or a CNV associated with one or more of the genes set forth at Table 15, and can be used to detect the absence or presence of the CNV, and the size of the CNV, as described herein. The substrate can be, e.g., a two-dimensional substrate known in the art such as a glass slide, a wafer (e.g., silica or plastic), a mass spectroscopy plate, or a three-dimensional substrate such as a gel pad. In some embodiments, the probes are nucleic acid capture probes.

Methods for generating arrays are known in the art and include, e.g., photolithographic methods (see, e.g., U.S. Pat. Nos. 5,143,854; 5,510,270; and 5,527,681, each of which is incorporated by reference in its entirety), mechanical methods (e.g., directed-flow methods as described in U.S. Pat. No. 5,384,261), pin-based methods (e.g., as described in U.S. Pat. No. 5,288,514, incorporated by reference in its entirety), and bead-based techniques (e.g., as described in PCT US/93/04145, incorporated by reference in its entirety). The array typically includes oligonucleotide probes capable of specifically hybridizing to different polymorphic variants. According to the method, a nucleic acid of interest, e.g., a nucleic acid encompassing a polymorphic site, (which is typically amplified) is hybridized with the array and scanned. Hybridization and scanning are generally carried out according to standard methods. After hybridization and washing, the array is scanned to determine the position on the array to which the nucleic acid from the sample hybridizes. The hybridization data obtained from the scan is typically in the form of fluorescence intensities as a function of location on the array.

Arrays can include multiple detection blocks (i.e., multiple groups of probes designed for detection of particular polymorphisms). Such arrays can be used to analyze multiple different polymorphisms, e.g., distinct polymorphisms at the same polymorphic site or polymorphisms at different chromosomal sites. Detection blocks may be grouped within a single array or in multiple, separate arrays so that varying conditions (e.g., conditions optimized for particular polymorphisms) may be used during the hybridization.

Additional description of use of oligonucleotide arrays for detection of polymorphisms can be found, for example, in U.S. Pat. Nos. 5,858,659 and 5,837,832, each of which is incorporated by reference in its entirety.

Results of the CNV profiling performed on a sample from a subject (test sample) may be compared to a biological sample(s) or data derived from a biological sample(s) that is known or suspected to be normal (“reference sample” or “normal sample”). In some embodiments, a reference sample is a sample that is not obtained from an individual having deletion or duplication syndrome, or would test negative in the particular one or more CNVs probed for in the test sample. The reference sample may be assayed at the same time, or at a different time from the test sample.

The results of an assay on the test sample may be compared to the results of the same assay on a reference sample. In some cases, the results of the assay on the reference sample are from a database, or a reference. In some cases, the results of the assay on the reference sample are a known or generally accepted value or range of values by those skilled in the art. In some cases the comparison is qualitative. In other cases the comparison is quantitative. In some cases, qualitative or quantitative comparisons may involve but are not limited to one or more of the following: comparing fluorescence values, spot intensities, absorbance values, chemiluminescent signals, histograms, critical threshold values, statistical significance values, CNV presence or absence, CNV size.

In one embodiment, an odds ratio (OR) is calculated for each individual CNV measurement. Here, the OR is a measure of association between the presence or absence of an SNP, and an outcome, e.g., deletion or duplication syndrome positive or negative, or likely to respond to therapy for the respective deletion or duplication syndrome. Odds ratios are most commonly used in case-control studies. For example, see, J. Can. Acad. Child Adolesc. Psychiatry 2010; 19(3): 227-229, which is incorporated by reference in its entirety for all purposes. Odds ratios for each CNV can be combined to make an ultimate diagnosis, to select a patient for treatment of a deletion or duplication syndrome, or to predict whether a subject is likely to respond to therapy for a deletion or duplication syndrome, for example, a deletion or duplication syndrome associated with developmental delay.

In one embodiment, a specified statistical confidence level may be determined in order to provide a diagnostic confidence level. For example, it may be determined that a confidence level of greater than 90% may be a useful predictor of the presence of a deletion or duplication syndrome, or to predict whether a subject is likely to respond to therapy for a deletion or duplication syndrome. In other embodiments, more or less stringent confidence levels may be chosen. For example, a confidence level of about or at least about 50%, 60%, 70%, 75%, 80%, 85%, 90%, 95%, 97.5%, 99%, 99.5%, or 99.9% may be chosen as a useful phenotypic predictor. The confidence level provided may in some cases be related to the quality of the sample, the quality of the data, the quality of the analysis, the specific methods used, and/or the number of CNVs analyzed. The specified confidence level for providing a diagnosis may be chosen on the basis of the expected number of false positives or false negatives and/or cost. Methods for choosing parameters for achieving a specified confidence level or for identifying markers with diagnostic power include but are not limited to Receiver Operating Characteristic (ROC) curve analysis, binomial ROC, principal component analysis, odds ratio analysis, partial least squares analysis, singular value decomposition, least absolute shrinkage and selection operator analysis, least angle regression, and the threshold gradient directed regularization method.

CNV detection may in some cases be improved through the application of algorithms designed to normalize and or improve the reliability of the data. In some embodiments of the present disclosure the data analysis requires a computer or other device, machine or apparatus for application of the various algorithms described herein due to the large number of individual data points that are processed. A “machine learning algorithm” refers to a computational-based prediction methodology, also known to persons skilled in the art as a “classifier,” employed for characterizing a CNV profile. The signals corresponding to certain CNVs, which are obtained by, e.g., microarray-based hybridization assays, sequencing assays, NanoString assays, etc., are in one embodiment subjected to the algorithm in order to classify the profile. Supervised learning generally involves “training” a classifier to recognize the distinctions among classes (e.g., CNV present, CNV absent, deletion syndrome positive, deletion syndrome negative, duplication syndrome positive, duplication syndrome negative) and then “testing” the accuracy of the classifier on an independent test set. For new, unknown samples the classifier can be used to predict the class (e.g., CNV present, CNV absent, deletion syndrome positive, deletion syndrome negative, duplication syndrome positive, duplication syndrome negative) in which the samples belong.

In some embodiments, a robust multi-array average (RMA) method may be used to normalize raw data. The RMA method begins by computing background-corrected intensities for each matched cell on a number of microarrays. In one embodiment, the background corrected values are restricted to positive values as described by Irizarry et al. (2003). Biostatistics April 4 (2): 249-64, incorporated by reference in its entirety for all purposes. After background correction, the base-2 logarithm of each background corrected matched-cell intensity is then obtained. The background corrected, log-transformed, matched intensity on each microarray is then normalized using the quantile normalization method in which for each input array and each probe value, the array percentile probe value is replaced with the average of all array percentile points, this method is more completely described by Bolstad et al. Bioinformatics 2003, incorporated by reference in its entirety. Following quantile normalization, the normalized data may then be fit to a linear model to obtain an intensity measure for each probe on each microarray. Tukey's median polish algorithm (Tukey, J. W., Exploratory Data Analysis. 1977, incorporated by reference in its entirety for all purposes) may then be used to determine the log-scale intensity level for the normalized probe set data.

Various other software programs may be implemented. In certain methods, feature selection and model estimation may be performed by logistic regression with lasso penalty using glmnet (Friedman et al. (2010). Journal of statistical software 33(1): 1-22, incorporated by reference in its entirety). Raw reads may be aligned using TopHat (Trapnell et al. (2009). Bioinformatics 25(9): 1105-11, incorporated by reference in its entirety). In methods, top features (N ranging from 10 to 200) are used to train a linear support vector machine (SVM) (Suykens J A K, Vandewalle J. Least Squares Support Vector Machine Classifiers. Neural Processing Letters 1999; 9(3): 293-300, incorporated by reference in its entirety) using the e1071 library (Meyer D. Support vector machines: the interface to libsvm in package e1071. 2014, incorporated by reference in its entirety). Confidence intervals, in one embodiment, are computed using the pROC package (Robin X, Turck N, Hainard A, et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC bioinformatics 2011; 12: 77, incorporated by reference in its entirety).

In addition, data may be filtered to remove data that may be considered suspect. In one embodiment, data derived from microarray probes that have fewer than about 4, 5, 6, 7 or 8 guanosine+cytosine nucleotides may be considered to be unreliable due to their aberrant hybridization propensity or secondary structure issues. Similarly, data deriving from microarray probes that have more than about 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, or 22 guanosine+cytosine nucleotides may be considered unreliable due to their aberrant hybridization propensity or secondary structure issues.

In some embodiments of the present invention, data from probe-sets may be excluded from analysis if they are not identified at a detectable level (above background).

In some embodiments of the present disclosure, probe-sets that exhibit no, or low variance may be excluded from further analysis. Low-variance probe-sets are excluded from the analysis via a Chi-Square test. In one embodiment, a probe-set is considered to be low-variance if its transformed variance is to the left of the 99 percent confidence interval of the Chi-Squared distribution with (N−1) degrees of freedom. (N−1)*Probe-set Variance/(Gene Probe-set Variance). about.Chi-Sq(N−1) where N is the number of input CEL files, (N−1) is the degrees of freedom for the Chi-Squared distribution, and the “probe-set variance for the gene” is the average of probe-set variances across the gene. In some embodiments of the present invention, probe-sets for a given CNV or group of CNVs may be excluded from further analysis if they contain less than a minimum number of probes that pass through the previously described filter steps for GC content, reliability, variance and the like. For example in some embodiments, probe-sets for a given gene or transcript cluster may be excluded from further analysis if they contain less than about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or less than about 20 probes.

Methods of CNV data analysis in one embodiment, further include the use of a feature selection algorithm as provided herein. In some embodiments of the present invention, feature selection is provided by use of the LEMMA software package (Smyth, G. K. (2005). Limma: linear models for microarray data. In: Bioinformatics and Computational Biology Solutions using R and Bioconductor, R. Gentleman, V. Carey, S. Dudoit, R. Irizarry, W. Huber (eds.), Springer, New York, pages 397-420, incorporated by reference in its entirety for all purposes).

Methods of CNV data analysis, in one embodiment, include the use of a pre-classifier algorithm. For example, an algorithm may use a specific molecular fingerprint to pre-classify the samples according to their composition and then apply a correction/normalization factor. This data/information may then be fed in to a final classification algorithm which would incorporate that information to aid in the final diagnosis.

Methods of CNV data analysis, in one embodiment, further include the use of a classifier algorithm as provided herein. In one embodiment of the present invention, a diagonal linear discriminant analysis, k-nearest neighbor algorithm, support vector machine (SVM) algorithm, linear support vector machine, random forest algorithm, or a probabilistic model-based method or a combination thereof is provided for classification of microarray data. In some embodiments, identified markers that distinguish samples (e.g., CNV duplication present vs. CNV duplication absent; CNV deletion present vs. CNV deletion absent; CNV size “n” vs. CNV size “x”, where “x” and “n” are the length in bases or basepairs of the CNV) are selected based on statistical significance of the difference in expression levels between classes of interest. In some cases, the statistical significance is adjusted by applying a Benjamin Hochberg or another correction for false discovery rate (FDR).

In some cases, the classifier algorithm may be supplemented with a meta-analysis approach such as that described by Fishel and Kaufman et al. 2007 Bioinformatics 23(13): 1599-606, incorporated by reference in its entirety for all purposes. In some cases, the classifier algorithm may be supplemented with a meta-analysis approach such as a repeatability analysis.

Methods for deriving and applying posterior probabilities to the analysis of microarray data are known in the art and have been described for example in Smyth, G. K. 2004 Stat. Appi. Genet. Mol. Biol. 3: Article 3, incorporated by reference in its entirety for all purposes. In some cases, the posterior probabilities may be used in the methods of the present invention to rank the markers provided by the classifier algorithm.

A statistical evaluation of the results of the molecular profiling may provide a quantitative value or values indicative of one or more of the following: the likelihood of the presence or absence of one or more CNVs; the likelihood of diagnostic accuracy of a deletion or duplication syndrome; the likelihood of a particular deletion or duplication syndrome; the likelihood of the success of a particular therapeutic intervention. In one embodiment, the data is presented directly to the physician in its most useful form to guide patient care, or is used to define patient populations in clinical trials or a patient population for a given medication. The results of the molecular profiling can be statistically evaluated using a number of methods known to the art including, but not limited to: the students T test, the two sided T test, pearson rank sum analysis, hidden Markov model analysis, analysis of q-q plots, principal component analysis, one way ANOVA, two way ANOVA, LIMMA and the like.

In some cases, accuracy may be determined by tracking the subject over time to determine the accuracy of the original diagnosis. In other cases, accuracy may be established in a deterministic manner or using statistical methods. For example, receiver operator characteristic (ROC) analysis may be used to determine the optimal assay parameters to achieve a specific level of accuracy, specificity, positive predictive value, negative predictive value, and/or false discovery rate.

In some cases the results of the CNV detection and sizing assays, are entered into a database for access by representatives or agents of a molecular profiling business, the individual, a medical provider, or insurance provider. In some cases assay results include sample classification, identification, or diagnosis by a representative, agent or consultant of the business, such as a medical professional. In other cases, a computer or algorithmic analysis of the data is provided automatically. In some cases the molecular profiling business may bill the individual, insurance provider, medical provider, researcher, or government entity for one or more of the following: molecular profiling assays performed, consulting services, data analysis, reporting of results, or database access.

In some embodiments of the present invention, the results of the CNV detection and sizing assays are presented as a report on a computer screen or as a paper record. In some embodiments, the report may include, but is not limited to, such information as one or more of the following: the number of CNVs identified as compared to the reference sample, the size of a CNV identified as compared to the size of the CNV in a reference sample (or reference database), the suitability of the original sample, a diagnosis, a statistical confidence for the diagnosis, the likelihood of a particular deletion or duplication syndrome, and proposed therapies.

The results of the CNV profiling may be classified into one of the following: CNV positive, CNV size (if CNV positive), CNV negative, deletion syndrome positive, deletion syndrome negative, non-diagnostic (providing inadequate information concerning the presence or absence of one or more CNVs or the size of one or more CNVs).

In some embodiments of the present invention, results are classified using a trained algorithm. Trained algorithms of the present invention include algorithms that have been developed using a reference set of known CNV and/or normal samples, for example, samples from individuals diagnosed with a particular deletion or duplication syndrome, or not diagnosed with the deletion or duplication syndrome. In some embodiments, training comprises comparison of one or more CNVs (presence and optionally size) in from a first CNV positive sample to the one or more CNVs in a second ASD positive sample, where the first set of CNVs include at least one CNV that is not in the second set.

Algorithms suitable for categorization of samples include but are not limited to k-nearest neighbor algorithms, support vector machines, linear discriminant analysis, diagonal linear discriminant analysis, updown, naive Bayesian algorithms, neural network algorithms, hidden Markov model algorithms, genetic algorithms, or any combination thereof.

When classifying a biological sample for diagnosis of a deletion or duplication syndrome, for example, WHS, or for the selection of a patient for treatment of a deletion or duplication syndrome, there are typically two possible outcomes from a binary classifier. When a binary classifier is compared with actual true values (e.g., values from a biological sample), there are typically four possible outcomes. If the outcome from a prediction is p (where “p” is a positive classifier output, such as the presence of a deletion or duplication syndrome) and the actual value is also p, then it is called a true positive (TP); however if the actual value is n then it is said to be a false positive (FP). Conversely, a true negative has occurred when both the prediction outcome and the actual value are n (where “n” is a negative classifier output, such as no deletion or duplication syndrome), and false negative is when the prediction outcome is n while the actual value is p. In one embodiment, consider a diagnostic test that seeks to determine whether a person has a certain deletion or duplication syndrome. A false positive in this case occurs when the person tests positive, but actually does not have the deletion or duplication syndrome. A false negative, on the other hand, occurs when the person tests negative, suggesting they are healthy, when they actually do have the disease (the deletion or duplication syndrome).

The positive predictive value (PPV), or precision rate, or post-test probability of disease, is the proportion of subjects with positive test results who are correctly diagnosed. It reflects the probability that a positive test reflects the underlying condition being tested for. Its value does however depend on the prevalence of the disease, which may vary. In one example the following characteristics are provided: FP (false positive); TN (true negative); TP (true positive); FN (false negative). False positive rate (□)=FP/(FP+TN)-specificity; False negative rate (□)=FN/(TP+FN)-sensitivity; Power=sensitivity=1−□□; Likelihood-ratio positive=sensitivity/(1−specificity); Likelihood-ratio negative=(1−sensitivity)/specificity. The negative predictive value (NPV) is the proportion of subjects with negative test results who are correctly diagnosed.

In some embodiments, the results of the CNV analysis of the subject methods provide a statistical confidence level that a given diagnosis is correct. In some embodiments, such statistical confidence level is at least about, or more than about 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% 99.5%, or more.

In one embodiment, depending on the results of the CNV hybridization assay and data analysis, the subject is selected for treatment for a particular deletion or duplication syndrome.

The present invention relates to diagnostic tests for determining whether a subject has a deletion or duplication syndrome, or predicting the presence or absence of one or more of the deletion or duplication syndromes set forth in Tables A and B. The diagnostic tests described herein may be an in vitro diagnostic test. Diagnostic tests include but are not limited to FDA approved, or cleared, In Vitro Diagnostic (IVD), Laboratory Developed Test (LDT), or Direct-to-Consumer (DTC) tests, that may be used to assay a sample and detect or indicate the presence of, the predisposition to, or the risk of, diseases, disorders, conditions, infections and/or therapeutic responses. In one embodiment, a diagnostic test may be used in a laboratory or other health professional setting. In another embodiment, a diagnostic test may be used by a consumer at home. Diagnostic tests comprise one or more reagents for detecting the presence or absence of the one or more CNV genetic markers associated with the particular deletion or duplication syndrome and may comprise other reagents, instruments, and systems intended for use in the in vitro diagnosis of disease or other conditions, including a determination of the state of health, in order to cure, mitigate, treat, or prevent disease. In one embodiment, the diagnostic tests described herein may be intended for use in the collection, preparation, and examination of specimens taken from the human body. In certain embodiments, diagnostic tests and products may comprise one or more laboratory tests. As used herein, the term “laboratory test” means one or more medical or laboratory procedures that involve testing samples of blood, urine, or other tissues or substances in the body.

One aspect of the present invention comprises an in vitro test for determining the presence or absence of a deletion or duplication syndrome, or predicting the likelihood of a deletion or duplication syndrome in a subject comprising a reagent for detecting one or more CNV genetic markers associated with the deletion or duplication syndrome, wherein the at least one CNV genetic marker comprises: at least one CNV genetic marker present at the chromosome location set forth in Table A or Table B, or at least one CNV as set forth in Tables 3-4, 8-10, 12 and/or 13; wherein detection in a genetic sample from the subject of the at least one CNV indicates that the individual is affected with the deletion or duplication syndrome, or is predisposed to developing the deletion or duplication syndrome.

In one embodiment the at least one CNV in Table A or Table B, or at least one CNV as set forth in Tables 3-4, 8-10, 12 and/or 13 comprises one or more of the CNV genetic markers numbered 6, 8, 10, 16 and 22 in Table 3.

In one embodiment, a diagnostic test as described herein has a diagnostic yield for the deletion or duplication syndrome of about 8% to about 40%. Diagnostic yield refers to the percent of individuals with the diagnosis of ASD that will have an abnormal genetic test result and is equal to sensitivity. In this regard, the diagnostic test described herein may have a diagnostic yield for ASD of about 8% to about 14%, from about 9% to about 13%, or from about 10% to about 12%. In further embodiments, a diagnostic test as described herein has a diagnostic yield for ASD of at least about 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20%, 21%, 22%, 23%, 24%, 25%, 26%, 27%, 28%, 29%, 30%, 31%, 32%, 33%, 34%, 35%, 36%, 37%, 38%, 39% or at least about 40%.

In certain embodiments, the CNV genetic markers associated with ASD as described herein may be isolated, amplified, and/or cloned into a vector. The term “vector” relates to a single or double stranded circular nucleic acid molecule that can be infected, transfected or transformed into cells and replicate independently or within the host cell genome. A circular double stranded nucleic acid molecule can be cut and thereby linearized upon treatment with restriction enzymes. An assortment of vectors, restriction enzymes, and the knowledge of the nucleotide sequences that are targeted by restriction enzymes are readily available to those skilled in the art, and include any replicon, such as a plasmid, cosmid, bacmid, phage or virus, to which another genetic sequence or element (either DNA or RNA) may be attached so as to bring about the replication of the attached sequence or element. A nucleic acid molecule of the invention (e.g., an isolated nucleic acid containing a CNV associated with ASD as described herein) can be inserted into a vector by cutting the vector with restriction enzymes and ligating the two pieces together.

Many techniques are available to those skilled in the art to facilitate transformation, transfection, or transduction of an expression construct into a prokaryotic or eukaryotic organism. The terms “transformation”, “transfection”, and “transduction” refer to methods of inserting a nucleic acid and/or expression construct into a cell or host organism. These methods involve a variety of techniques known to the skilled artisan, such as treating the cells with high concentrations of salt, an electric field, or detergent, to render the host cell outer membrane or wall permeable to nucleic acid molecules of interest, microinjection, PEG-fusion, and the like.

Those skilled in the art will recognize that a nucleic acid vector can contain nucleic acid elements other than the promoter element and the autism specific marker gene nucleic acid molecule. These other nucleic acid elements include, but are not limited to, origins of replication, ribosomal binding sites, nucleic acid sequences encoding drug resistance enzymes or amino acid metabolic enzymes, and nucleic acid sequences encoding secretion signals, localization signals, or signals useful for polypeptide purification.

In one embodiment, the methods and in vitro diagnostic tests and products described herein may be used for the diagnosis of a deletion or duplication syndrome, patients with non-specific symptoms possibly associated with the deletion or duplication syndrome, and/or patients presenting with related disorders. In another embodiment, the methods and in vitro diagnostic tests described herein may be used for screening for risk of progressing from at-risk, non-specific symptoms possibly associated with the deletion or duplication syndrome, and/or fully-diagnosed ASD. In certain embodiments, the methods and in vitro diagnostic tests described herein can be used to rule out screening of diseases and disorders that share symptoms with the deletion or duplication syndrome. In yet another embodiment, the methods and in vitro diagnostic tests described herein may indicate diagnostic information to be included in the current diagnostic evaluation in patients suspected of having the deletion or duplication syndrome.

In one embodiment, a diagnostic test may comprise one or more devices, tools, and equipment configured to collect a genetic sample from an individual. In one embodiment of a diagnostic test, tools to collect a genetic sample may include one or more of a swab, a scalpel, a syringe, a scraper, a container, and other devices and reagents designed to facilitate the collection, storage, and transport of a genetic sample. In one embodiment, a diagnostic test may include reagents or solutions for collecting, stabilizing, storing, and processing a genetic sample. Such reagents and solutions for collecting, stabilizing, storing, and processing genetic material are well known by those of skill in the art. In another embodiment, a diagnostic test as disclosed herein, may comprise a microarray apparatus and associated reagents, a flow cell apparatus and associated reagents, a multiplex next generation nucleic acid sequencer and associated reagents, and additional hardware and software necessary to assay a genetic sample for the presence of certain genetic markers and to detect and visualize certain genetic markers.

In certain embodiments, one or more CNV genetic markers described herein can be used in a method for selecting a patient for treatment of a mitochondrial associated disorder, or a disorder associated with a genetic duplication and/or deletion, for example, Wolf-Hirshhorn Syndrome (WHS). For example, the patient is selected for treatment of the deletion or duplication syndrome depending on the presence or absence of the particular CNV(s) that is probed for, and optionally, if the CNV(s) is present, the size of the CNV (e.g., as compared to a reference value) is taken into consideration in order to select the patient for therapy.

In one embodiment, the patient is selected for treatment with gene therapy, RNA interference (RNAi), behavioral therapy (e.g., Applied Behavior Analysis (ABA), Discrete Trial Training (DTT), Early Intensive Behavioral Intervention (EIBI), Pivotal Response Training (PRT), Verbal Behavior Intervention (VBI), and Developmental Individual Differences Relationship-Based Approach (DIR)), physical therapy, occupational therapy, sensory integration therapy, speech therapy, music therapy, the Picture Exchange Communication System (PECS), dietary treatment, or drug therapy (e.g., antipsychotics, anti-depressants, anticonvulsants, stimulants, aripiprazole, guanfacine, selective serotonin reuptake inhibitors (SSRIs), riseridone, olanzapine, naltrexone).

In the case of gene therapy treatment, in one embodiment, the gene therapy comprises delivery to the subject the wild type sequence of a particular gene that has been detected as part of a CNV in the patient.

Where a CNV that is associated with a mitochondrial gene is detected in a subject, the subject is selected for therapy with one or more of the following: EPI-743, antioxidants, oxygen, arginine, Coenzyme Q10, idebenone, benzoquinone therapeutics (e.g., alpha-tocotrien).

Where a CNV that is associated with glutamate or GABA receptor is detected in a subject, the subject, in one embodiment, is selected for therapy with a glutamate receptor agonist or antagonist or a GABA receptor agonist or antagonist. In a further embodiment, the subject is selected for therapy with a glutamatergic receptor agonist or GABAergic antagonist if the effect of the CNV is an inhibitory effect, and wherein the subject is administered a glutamatergic receptor antagonist or GABAergic agonist if the effect of the CNV is an excitatory effect.

EXAMPLES

The present invention is further illustrated by reference to the following Example. However, it should be noted that these Examples, like the embodiments described above, are illustrative and are not to be construed as restricting the scope of the invention in any way. The references cited in the Example are incorporated by reference in their entireties for all purposes

Example 1 Identification of Rare Recurrent Copy Number Variants in High-Risk Autism Families and their Prevalence in a Large ASD Population

Genetics are known to play a major role in individuals with autism. However, the genetic underpinnings of autism are highly complex. The study described in this example used high-risk autism families to identify genetic variants that could predispose to autism in these families. This study also further evaluated these variants in a very large group of unrelated autism samples and controls to determine if these variants were relevant to children with autism in the broader population. This study identified 18 genetic variants that have not previously been observed in children with autism that are important not only in families but also in unrelated children with autism. By using a very large group of samples and controls this study also provides better frequency and significance estimates for many genetic variants previously associated with autism. This study sets the stage for using these genetic variants in the clinical analysis of children with autism.

Structural variation is thought to play a major etiological role in the development of ASDs, and numerous studies documenting the relevance of copy number variants in ASDs have been published since 2006. To determine if large ASD families harbor high-impact CNVs that may have broader impact in the general ASD population, the present experiments used the Affymetrix genome wide human SNP array 6.0 to identify 153 putative autism-specific CNVs present in 55 individuals with ASD from 9 multiplex ASD pedigrees. To evaluate the actual prevalence of these CNVs as well as 185 CNVs reportedly associated with ASD from published studies many of which are insufficiently powered, a custom Illumina array was designed and used to interrogate these CNVs in 3,000 ASD cases and 6,000 controls.

Additional single nucleotide variants (SNVs) on the array identified 25 CNVs not detected in the family studies at the standard SNP array resolution. After molecular validation, the results demonstrated that 15 CNVs identified in high-risk ASD families also were found in two or more ASD cases with odds ratios greater than 2.0, strengthening their support as ASD risk variants. In addition, of the 25 CNVs identified using SNV probes on the custom array, 9 also had odds ratios greater than 2.0, suggesting that these CNVs also are ASD risk variants. Eighteen of the validated CNVs have not been reported previously in individuals with ASD and three have only been observed once. Finally, the results described here confirmed the association of 31 of 185 published ASD-associated CNVs in this dataset with odds ratios greater than 2.0, suggesting they may be of clinical relevance in the evaluation of children with ASDs. Taken together, these data provide strong support for the existence and application of high-impact CNVs in the clinical genetic evaluation of children with ASD.

Twin studies [1-3], (reviewed in [4]), family studies [5-7], and reports of chromosomal aberrations in individuals with ASD (reviewed in [8]) all have strongly suggested a role for genes in the development of ASD. Although the magnitude of the genetic effect observed in ASD varies from study to study, it is clear that genetics plays a significant role.

While a number of genes associated with ASD susceptibility have been observed in multiple studies, variants in a single gene cannot explain more than a small percentage of cases. Indeed, recent estimates suggest that there may be nearly 400 genes or chromosomal regions involved in ASD predisposition [9-12].

In the past few years, a number of studies have identified both de novo and inherited structural variants, CNVs, that are associated with ASD [13-23]. De novo CNVs may explain at least some of the “missing heritability” of ASD as understood to date. While it is clear that CNVs play an important role in susceptibility to ASD, it is also clear that the genetic penetrance of many of these CNVs is less than 100%. Although many of the duplications or deletions observed in children with ASD occur as de novo variants, duplications, for example on chromosome 16p11.2, often are inherited from an asymptomatic parent. Moreover, both deletions and duplications encompassing a portion of chromosome 16p11.2 have been associated with ASD [21, 24-26] and 16p11.2 gains have been associated with ADHD and schizophrenia [24, 27-29], indicating that the same genomic region can be involved in multiple developmental conditions. In addition, deletions on chromosome 7q11.23 are known to cause Williams syndrome and duplications of this same region have been observed and are thought to be causal in individuals with ASD [9,11]. While individuals with Williams syndrome tend to be outgoing and social, individuals with ASD are socially withdrawn, suggesting that deletions and duplications in this region result in individuals on opposite sides of the behavioral spectrum.

Although numerous studies regarding the role of CNVs in ASD have been published in the research literature, the findings of these studies have not been fully utilized for clinical evaluation of children with ASD. This is likely due to the rarity of individual variants, the lack of probe coverage on clinical microarrays that permits detection of smaller variants, and the difficulty in understanding the relevant biology of some variants even when they are significantly associated with ASD. Despite this, published clinical guidelines suggest that microarray-based testing should be the first step in the genetic analysis of children with syndromic and non-syndromic ASD as well as other conditions of childhood development [30], and there is a wealth of information demonstrating its utility in large samples of children who have undergone such testing [25,31].

This example describes efforts to discover high-impact CNVs in high-risk ASD families in Utah and to assess their potential role in unrelated ASD cases. These CNVs were interrogated, as well as CNVs from multiple published sources [18,32] in a large sample set of ASD cases and controls, to determine more precisely their potential disease relevance. To evaluate carefully these CNVs, a custom Illumina iSelect array was designed containing probes within and flanking CNV regions of interest. This custom array was used to obtain high-quality CNV results on 2,175 children with clinically diagnosed ASD and 5,801 children with normal development following removal of samples that did not meet stringent quality control parameters. The results of this study identify multiple rare recurrent CNVs from high-risk ASD families that also confer risk in unrelated ASD cases and delineate the prevalence and impact of CNVs reported in the literature in a large case control study of ASDs.

DNA Samples.

DNA samples from high-risk ASD family members were collected after obtaining informed consent using a University of Utah IRB-approved protocol. Three independent sample cohorts, comprising 3,000 ASD patient samples (72% male), were collected for CNV replication. Of those, 857 were probands recruited and genotyped by the Center for Applied Genomics (CAG) at The Children's Hospital of Philadelphia (CHOP) from the greater Philadelphia area using a CHOP IRB-approved protocol; 2,143 ASD samples were from the AGRE and the AGP consortium (Rutgers, N.J. ASD repository), and genotyped at the CAG center at CHOP (Table 1). Only samples from affected individuals diagnosed using the Autism Diagnostic Interview-Revised (ADI-R) and the Autism Diagnostic Observation Schedule (ADOS) were used in the study. All control samples were from CHOP and were matched in a 2:1 ratio with the ASD cases.

TABLE 1 Case and control samples used in this study. case control female male female AGRE/AGP 1,517 626 0 0 CHOP 633 224 3,992 2,008 sub-total 2,150 850 3,992 2,008 grand-total 3,000 6,000

CNV Discovery in High-Risk ASD Families.

DNA samples were genotyped on the Affymetrix Genome-Wide Human SNP Array 6.0 according to the manufacturer's protocol. Fifty-five autism subjects were chosen from 9 families with multiple affected first-degree relatives. The number of individuals with an autism diagnosis in these families ranged from 3 to 9. Affected individuals were diagnosed using ADI-R and ADOS. Control subjects (N=439) for the discovery phase of the project were selected from Utah CEPH/Genetics Reference Project (UGRP) families [70]. All microarray experiments were performed on blood DNA samples, except for two of the 55 case samples and three control subjects for which DNA from lymphoblastoid cell lines was used. CNVs were initially detected using the Copy Number Analysis Module (CNAM) of Golden Helix SNP & Variation Suite (SVS) (Golden Helix Inc.). Log ratios were calculated by quantile normalizing the A allele and B allele intensities using the entire population as a reference median for each SNP.

Batch effects in the log ratios were corrected via numeric principle component analysis (PCA) [71]. CNV segmentation analysis was carried out for each individual using the univariate CNAM segmentation procedure of Golden Helix SVS. We used a moving window of 5,000 markers, maximum number of segments per window of 20, minimum segment size 10 markers, and pairwise permutation p-value of 0.001.

iSelect Array Design.

Probes for each CNV to be characterized in this study were selected from the Illumina Omni2.5 array probe set. Probes were selected to be as uniformly spaced across each region and flanking each region as possible (using the hg19 genome build). For each CNV, we included 10 or more probes within the defined CNV region (CNVr) and five probes on each flank (except where not possible due to the telomeric location of a CNVr). Probes for an additional 185 CNVs described in the literature, including 104 identified by CHOP in samples that partially overlap those used in this study, also were included for further CNV validation. We attempted to increase probe coverage for CNVs identified with only a small number of probes. Probes for 2,799 putative functional candidate SNVs detected by targeted exome DNA sequencing on 26 representative individuals from 11 ASD families (unpublished data) were included. The genes that were targeted for exome sequencing included all known genes in regions of familial haplotype sharing and linkage as well as additional autism candidate genes. These SNVs, although included in a search for potential ASD point mutations, also were used to identify additional CNVs.

Array Processing.

High throughput SNP genotyping using the Illumina Infinium™ II BeadChip technology (Illumina, San Diego), at the Center for Applied Genomics at CHOP was performed. Detailed methods for array processing are described in the section entitled Supplemental Materials below.

CNV Calling and Statistical Analysis.

CNVs were called using both PennCNV [34,35] and CNAM (Golden Helix SNP & Variation Suite (SVS), Golden Helix, Inc.). CNV calling using PennCNV was performed as described [32]. For CNAM calls, each target region was separately analyzed, rather than whole chromosomes. Since our array targeted specific regions and did not have probe coverage over much of the genome, it was desirable to avoid calling segments that spanned large regions with no data, and prevent any CNV calls from being influenced by distant data points. To accomplish this, the markers in the data set were grouped into “pseudochromosomes”, one for each CNV covered by the array, that were then considered individually in the segmentation algorithm. After segmentation, segments were classified as losses, gains, or neutral. Fisher's exact test was used to test for association of copy number loss versus no loss, and copy number gain versus no gain. Similar tests were conducted for the X chromosome, stratified by gender. Odds ratios also were calculated as an indicator of potential clinical risk for each CNV.

Laboratory Confirmation of CNVs.

Array results were confirmed using pre-designed Applied Biosystems TaqMan copy number assays or custom-designed TaqMan copy number assays when necessary (Life Technologies, Inc.). All CNVs with odds ratios greater than 2.0 and present in at least two cases were selected for molecular validation. We did not select CNVs with odds ratios less than 2 were not selected for validation because these odds ratios were not thought to have high potential clinical utility. Six CNVs were also selected for validation because they were adjacent to, but not overlapping, literature CNVs that were covered by probes on the custom array. A maximum of 6 case samples were validated for each CNV. Five negative control samples, selected based on their lack of all of the CNVs under study also were included in each validation assay. A list of all of the TaqMan assays used in this work is found in Table 7, and detailed procedures of the TaqMan assays are described in the supplemental methods.

Pathway Analysis.

Analysis of biological pathways encompassing genes found in the CNV regions was performed using the bioinformatics tools DAVID Bioinformatics Resources 6.7 [72,73] and Ingenuity Pathways Analysis (IPA) (Ingenuity® Systems). Network and pathway analyses on genes contained within the CNVs or immediately flanking intergenic CNVs that were PCR validated was performed. Pathway analysis details are described in the supplemental methods.

CNV Discovery in Utah High Risk Autism Pedigrees.

Using CNAM (GoldenHelix Inc.) on Affymetrix Genome-Wide Human SNP array 6.0 data, a total of 153 CNVs in subjects with autism in Utah families that were not found in any CEPH/UGRP control samples were identified. This set included 131 novel CNVs and 22 CNVs present in the Autism Chromosomal Rearrangement Database [15]. Thirty-two autism-specific CNVs were detected in multiple (2 or more) autism subjects, and 121 CNVs were detected in only one person among the 55 autism subjects assayed. Of these, 153 CNVs, 112 were copy number losses (deletions) and 41 were copy number gains (duplications). The average size of the CNVs from high-risk families was 91 kb. The genomic locations of these CNVs are shown in Table 8.

CNV Regions on the Custom Array.

To better understand the frequency of the CNVs identified in Utah ASD families in a broader ASD population, we created a custom Illumina iSelect array containing probes covering all 153 of the Utah CNVs described in Table 8. CNV coordinate, copy number status, and probe content for each CNV are included. In addition, since the ultimate goal of this work is to understand the frequency and relevance of rare recurrent CNVs in the etiology of ASD, we included probes for 185 autism-associated CNVs identified in the literature [14-16, 18, 21, 32, 33] (Table 9). The probe coverage for each literature CNV also is shown in Table 9. In total, 7134 probes, all selected from the Illumina 2.5M array, were used for this study. As part of a separate study we also included 2799 SNVs detected by next-generation sequencing of genes in regions of haplotype sharing among our high-risk ASD families and in published ASD candidate genes in these same individuals also were included. Intensity data for these SNVs were used to identify additional CNVs that were not observed in our Utah high-risk ASD families (Table 10). Following standard data QC steps (see supplemental results) this array was used to characterize which of these 363 CNVs were present in DNA from 2,175 children with autism and 5,801 age, gender, and ethnicity matched controls (Table 1). These 7976 samples were available for analysis following our strict quality control measures (supplemental methods).

Analysis of CNVs on the iSelect Array.

The workflow for CNV analyzis of the custom array data is shown in FIG. 1. Following quality control analysis, including removal of samples that did not meet laboratory sample quality control measures, samples with excessive CNV calls, samples of uncertain ethnicity, and related samples, our final dataset included 1544 unrelated cases and 5762 unrelated controls. Because of the inherent noisiness of CNV analysis, we used two independent CNV calling algorithms, PennCNV [34] and CNAM (Golden Helix, Inc.), to increase our ability to detect CNVs. We identified 6,086 CNVs in cases and 14,387 CNVs in controls using PennCNV and 3,226 CNVs in cases and 8,234 CNVs in controls using CNAM. 1,537 CNVs from the 2175 cases including those from multiplex families (average 0.70 CNVs per individual) and 3,845 CNVs from the 5801 controls including related controls (average of 0.66 CNVs per individual) were called by both algorithms used for CNV detection.

All CNV regions harboring CNVs shared among subjects were defined from PennCNV calls, CNAM calls and the PennCNV/CNAM intersecting calls and their significance of association was calculated across the genome (FIG. 2). Of the 153 CNVs discovered in high-risk ASD families, 139 of them were seen in replication samples evaluated with the custom Illumina iSelect array. Seven of the CNVs not seen in this larger population study had poor probe coverage on the array either due to their small size or their genomic content, while the remainder that were not detected may represent false positive CNVs from our initial discovery work or may be rare CNVs that are private to the families or individuals in which they were identified.

Molecular Validation of CNV Calls.

We used TaqMan copy number assays to confirm the presence of CNVs in our population. A summary of the 195 TaqMan assays used is shown in Table 7 (Hs assay names refer to assays available from Applied Biosystems, now Life Technologies, Carlsbad, Calif.). Since our goal for this study was to understand the frequencies of these CNVs in a large case/control population, we chose to validate any CNVs that were likely to have clinical relevance. Our criteria for selection were as follows: 1) any CNV with an odds ratio>=2.0; 2) any rare CNV seen in at least two cases. These criteria for selecting CNVs were chosen to validate because the goal was to translate research CNV findings into potentially clinically useful markers. Since clinical testing of individuals with ASD is only performed on people who are symptomatic, CNVs with odds ratios <1.0 (CNVs that indicate lower than average risk of ASD) were not chosen for validation. Likewise, since CNVs with odds ratios>=1 but <=2 do are not of great diagnostic interest, we chose to validate only CNVs with odds ratios>=2.0. By using these criteria, we included rare recurrent CNVs that may be etiologically important despite the lack of statistical significance in cases versus controls. For previously published CNVs we considered our custom Illumina iSelect array as an independent test of their validity. We assumed therefore that these CNVs did not require additional testing. Since some of the CNVs from CHOP were not included in previous publications [18,32], we selected all CHOP CNVs for molecular validation. For CNVs that met our selection criteria we assayed a maximum of six case samples that contained the CNV, giving priority to those samples called both by PennCNV and CNAM. Results of these TaqMan experiments are summarized in Table 2. Interestingly, many of the most common CNVs detected by the array were not validated by the TaqMan assays. For example, when we tested samples from a statistically significant CNV duplication on chromosome 7q36.1 that was detected only by PennCNV and not by CNAM, all samples tested were shown to have two copies rather than the anticipated three copies, suggesting that in this sample set at least some of the CNV duplications observed are not true positives. Conversely all but one of the CNVs observed on chromosome 15, whether in the Prader-Willi/Angelman syndrome region or located more distally on chromosome 15, were confirmed by TaqMan assays. Results of these validation experiments demonstrated that CNVs called both by PennCNV and CNAM were much more likely to be confirmed (97% of tested samples) than CNVs called by either PennCNV alone (24%) or CNAM alone (30%). This observation demonstrates the care that must be taken during the CNV discovery process to insure that only valid calls are selected for further analysis.

False negative results also are possible with these microarray studies. However, the controls used for TaqMan assays were selected from the control sample set because they lacked CNV calls for any of the regions being evaluated. In none of these samples did the TaqMan results indicate the presence of any of the CNVs being validated, so no false negative results were detected. These data suggest that false negative results are not a common problem in this study.

TABLE 2 confirmation of CNV calls by quantitative PCR. TaqMan CNV Utah Family Utah Sequence Literature Validation Status CNVs SNP CNVs CNVs Total PASS 24 (2 overlap 15 25 64 with Lit. CNV) FAIL 9 9 5 23 NoCall 0 1 0 1 A summary of the PCR validation result is shown. Sequence SNP CNVs were discovered in this work using SNVs present on this array for sequence variant confirmation in the same cohort.

CNVs from High-Risk Utah Families.

One hundred thirty-nine of the 153 CNVs identified in high-risk ASD families were observed in case and/or control samples in this large dataset. Of these, 33 were present in two or more cases and had odds ratios greater than 2 and thus were selected for molecular confirmation. Following TaqMan validation, fifteen of thirty-three CNVs were confirmed (Table 3). This set included 3 CNVs with mixed results (Table 3). A CNV that was validated in some samples but not in others was considered to have passed validation if the validated samples resulted in an odds ratio greater than 2.0 with at least two confirmed cases, even if other samples did not pass molecular validation. The remaining 18 CNVs did not pass validation experiments.

One hundred thirty-nine of the 153 CNVs identified in high-risk ASD families were observed in case and/or control samples in this large dataset. Of these, 33 were present in two or more cases and had odds ratios greater than 2 and thus were selected for molecular confirmation. Following TaqMan validation, fifteen of the thirty-three CNVs were validated (Table 3). Of the 15 validated CNVs identified in high-risk families, 4 were shown to be inherited CNVs while three were de novo CNVs in the discovery families. The remainder were of undetermined origin, in most cases due to lack of information for one or both parents. A CNV that was validated in some samples but not in others, for example if a CNV was validated in all calls made by both PennCNV and CNAM but was not validated in all calls made only by one program, was considered to have passed validation if the validated samples yielded an odds ratio greater than 2.0 with at least two cases confirmed by validation.

Notable among these CNVs is a deletion observed near the 5′-end of the NRXN1 gene. This deletion, observed in five cases and only in one control, includes at least a portion of the NRXN1-alpha promoter, and extends into the first exon of NLRXN1-α, as shown in the UCSC Genome Browser view [35] (FIG. 3). CNVs impacting NRXN1 in ASD as well as other neurological conditions have been published by others [15, 32, 36-40], so the observation of NRXN1 CNVs both in our high-risk ASD family discovery work and in the large case/control replication study demonstrates our ability to detect biologically relevant CNVs that may also have clinical utility.

Other CNVs of interest included portions of the LINGO2 and STXBP5 genes. Single nucleotide variants in the LINGO2 gene have been associated with essential tremor and with Parkinson's disease, suggesting that the LINGO2 protein may have a neurological function [41]. However, CNVs in this gene have not previously been identified in individuals with ASD. We also observed deletions involving a portion of the STXBP5 gene, an interesting finding based on the potential role of STXBP5 in neurotransmitter release [42,43].

CNVs Identified by SNV Probes.

Twenty-five additional CNVs shown in Table 3 were discovered using SNVs identified in our high-risk ASD families. The SNVs that detected these twenty-five CNVs (Table 10) were identified by exon capture and DNA sequencing in regions of haplotype sharing and in published ASD candidate genes in our high-risk ASD families, and were selected for further study because they might alter the function of the proteins in which they were found (unpublished observations). The 9 validated CNVs derived from SNV intensity data are shown in Table 3 (CNVs not detected in discovery cohort). One of these CNVs, a chromosome 15q duplication, encompasses three duplication CNVs in Table 10. These three CNVs are thought to be contiguous since TaqMan data confirmed the same samples to be positive for each of them.

Interestingly, duplications involving the GABA receptor gene cluster, as well as many other genes, on chromosome 15q12 Were observed in 11 unrelated cases in our study and only in a single control, shown in the UCSC Genome Browser view [35] (FIG. 4). Contrary to our findings, a recent search for CNVs in GABA pathway genes [44] did not find an enrichment of duplications in this region. Rather, both deletions and duplications were observed at similar frequencies in cases and controls.

Published CNVs.

Additional CNVs from the literature and both published and unpublished CNVs identified at CHOP also were observed in our large dataset and met our criteria for potential clinical utility. Of those, 31 high-impact CNVs are shown in Table 4 (CNVs 20 and 21 in Table 4 are shown separately but are noted as likely being contiguous and thus likely are only a single entity). All CNVs not previously experimentally validated were validated in this study.

One of the previously unpublished CHOP CNVs is a duplication that encompasses the 3′-end RGS20 gene as well as the 3′-end of the TCEA1 gene. The RGS gene family encodes proteins that regulate G-protein signaling. These proteins function by increasing the inherent GTPase activity of their target G-proteins, and thus limit the signaling activity of their target G-proteins by keeping them in the inactive, GDP-bound state. RGS20 is expressed throughout the brain (reviewed in [45]), making it a likely candidate for involvement in neurological development. The TCEA1 gene, which also is partially encompassed by this CNV, is a transcription elongation factor involved in RNA polymerase II transcription. A role for TCEA1 in cell growth regulation has been suggested [46]. This potential role is consistent with the involvement of TCEA1 CNVs in ASD etiology as well.

TABLE 3 Validated CNVs discovered using affected children from Utah families CNV CNV Region - CNV Region - CNV Odds No. Origin Cytoband Discovery Cohort Replication Cohort Type Ratio P Value Cases Controls Gene/Region 1 Utah CNV 1q21.1 chr1: 145714421- chr1: 145703115- Dup 3.37 9.60E−03 9 10 CD160, PDZK1 146101228 145736438 2 Utah CNV 1q41 chr1: 215858193- chr1: 215854466- Del 2.12 5.02E−03 22 39 USH2A 215861879 215861792 3 Utah CNV 2p16.3 chr2: 51272055- chr2: 51266798- Del 14.96  8.26E−03 4 1 upstream of 51336043 51339236 NRXN1 4 Utah CNV^(#) 3q26.31 chr3: 172596081- chr3: 172591359- Dup 3.74 2.11E−01 1 1 downstream of 172617355 172604675 SPATA16 5 Utah CNV^(#) 4q35.2 chr4: 189084983- chr4: 189084240- Del 3.74 1.98E−01 2 2 downstream of 189117429 189117031 TRIML1 6 Utah CNV^(#) 6p24.3 chr6: 7425246- chr6: 7461346- Del ∞ 2.11E−01 1 0 between RIOK1 7464367 7470321 and DSP 7 Utah CNV^(#) 6q11.1 chr6: 62443739- chr6: 62426827- Dup 3.74 1.98E−01 2 2 KHDRBS2 62462295 62472074 8 Utah CNV 6q24.3 chr6: 147588752- chr6: 147577803- Del ∞ 2.10E−01 1 0 STXBP5 147664671 147684318 9 Utah CNV^(#) 7p22.1 chr7: 6838712- chr7: 6870635- Dup 7.47 1.15E−01 2 1 upstream of 6864071 6871412 CCZ1B 10 Sequence 7q21.3 Not found chr7: 93070811- Del ∞ 4.46E−02 2 0 CALCR, MIR653, SNP CNV^(#) 93116320 MIR489 11 Utah CNV^(#) 9p21.1 chr9: 28190069- chr9: 28207468- Del 3.74 6.72E−02 4 4 LINGO2 28347679 28348133 12 Utah CNV^(#) 9p21.1 chr9: 28190069- chr9: 28354180- Del 3.73 3.78E−01 1 1 LINGO2 (intron) 28347679 28354967 13 Utah CNV 10q23.1 chr10: 83893626- chr10: 83886963- Del 3.76 1.54E−02 7 7 NRG3 (intron) 84175018 83888343 14 Utah CNV^(#) 10q23.31 chr10: 92274764- chr10: 92262627- Dup 7.47 1.15E−01 2 1 downstream of 92289762 92298079 BC037970 15 Utah CNV^(#) 12q23.2 chr12: 102097012- chr12: 102095178- Dup 7.47 1.15E−01 2 1 CHPT1 102106306 102108946 16 Utah CNV# 13q13.3 chr13: 40087689- chr13: 40089105- Del ∞ 2.11E−01 1 0 LHFP (intron) 40088007 40090197 17 Sequence 14q32.2 Not found chr14: 100705631- Dup 9.36 5.99E−03 5 2 SLC25A29, YY1, SNP CNV^(#) 100828134 MIR345, SLC25A47, WARS 18 Sequence 14q32.31 Not found chr14: 102018946- Dup 4.62 1.01E−14 60 50 DIO3AS, DIO3OS SNP CNV^(#) 102026138 19 Sequence 14q32.31 Not found chr14: 102729881- Del 7.47 1.15E−01 2 1 MOK SNP CNV^(#) 102749930 20 Sequence 14q32.31 Not found chr14: 102973910- Dup 3.82 8.29E−26 136 142 ANKRD9 (RAGE) SNP CNV^(#) 102975572 21 Sequence 15q11.2- Not found chr15: 25690465- Dup* 41.05  1.82E−08 11 1 ATP10A, GABRB3, SNP CNV q13.1 28513763 GABRA5, GABRG3. 22 Sequence 15q13.2- Not found chr15: 31092983- Del ∞ 4.46E−02 2 0 FAN1, MTMR10, SNP CNV^(#) 15q13.3 31369123 MIR211, TRPM1 23 Sequence 15q13.3 Not found chr15: 31776648- Dup 4.40 6.91E−06 21 18 OTUD7A SNP CNV^(#) 31822910 24 Sequence 20q11.22 Not found chr20: 32210931- Dup 2.72 3.16E−02 8 11 NECAB3, CBFA2T2, SNP CNV^(#) 32441302 C20orf144, NECAB3, CNVs shown here were selected based on their p value, their case/control odds ratio, or both and were subject to molecular validation. *This CNV is contiguous with the chromosome 15q11.2 CNV described in Table 4 based on TaqMan data. ^(#)Designates CNVs not previously seen in ASD, based on queries for genes included in or flanking the CNV. **Denotes gene in or adjacent to the CNV that is involved in neural function, development and disease (see Table 5-6).

TABLE 4 Published CNVs observed in the sample population Region of Literature Highest CNV TaqMan No. Cytoband CNVs Significance Type Validation OddsRatio P Value Cases Ctrls Gene/Region 1 1q21.1 chr1: 146555186- chr1: 146656292- Dup NT 7.48 1.15E−01 2 1 FMO5 147779086 146707824 2 2p24.3 chr2: 13202218- chr2: 13203874- Del Validated (chr2: ∞ 2.11E−01 1 0 upstream of 13248445 13209245 13203874- LOC100506474 13209245) 3 2p21 chr2: 45455651- chr2: 45489954- Dup NT ∞ 4.46E−02 2 0 between UNQ6975 45984915 45492582 and SRBD1 4 2p16.3 chr2: 50145644- chr2: 51237767- Del NT ∞ 1.99E−03 4 0 NRXN1** 51259671 51245359 5 2p15 chr2: 62258231- chr2: 62230970- Dup NT ∞ 2.11E−01 1 0 COMMD1 63028717 62367720 6 2q14.1 chr2: 115139568- chr2: 115133493- Del NT 7.47 1.15E−01 2 1 between 115617934 115140263 LOC440900 and DPP10** 7 3p26.3 chr3: 1940192- chr3: 1937796- Del Validated (chr3: 5.60 6.70E−02 3 2 between CNTN6 1940920 1941004 1937796- and CNTN4** 1942764) 8 3p14.1 chr3: 67656832- chr3: 67657429- Del NT ∞ 2.11E−01 1 0 SUCLG2, FAM19A4, 68957204 68962928 FAM19A1 9 4q13.3 chr4: 73756500- chr4: 73766964- Dup Validated (chr4: ∞ 2.11E−01 1 0 COX18, ANKRD17 73905356 73816870 73753294- 74058988) 10 4q33 chr4: 154087652- chr4: 171366005- Del NT ∞ 4.46E−02 2 0 between AADAT** 172339893 171471530 and HSP90AA6P 11 5q23.1 chr5: 118478541- chr5: 118527524- Dup Validated (chr5: 3.74 1.98E−01 2 2 DMXL1, TNFAIP8 118584821 118589485 118527524- 118614781) 12 6p21.2 chr6: 39071841- chr6: 39069291- Del Validated (chr6: 2.37 1.93E−02 12 19 SAYSD1 39082863 39072241 39069291- 39072241) 13 8q11.23 chr8: 54858496- chr8: 54855680- Dup Validated (chr8: ∞ 2.11E−01 1 0 RGS20, TCEA1 54907579 54912001 54855680- 54912001) 14 10q11.22 chr10: 46269076- chr10: 49370090- Dup NT 3.77 1.96E−01 2 2 FRMPD2P1, 50892143 49471091 FRMPD2 15 10q11.23 chr10: 50892146- chr10: 50884949- Dup NT 3.74 1.98E−01 2 2 OGDHL, C10orf53 51450787 50943185 16 12q13.13 chr12: 53183470- chr12: 53177144- Del Validated (chr22: ∞ 4.46E−02 2 0 between KRT76 and 53189890 53180552 53177144- KRT3 53182177) 17 15q11.1 chr15: 20266959- chr15: 20192970- Dup Validated (chr15: 4.97 4.06E−02 4 3 downstream of 25480660 20197164 20192970- HERC2P3 20212798) 18 15q11.2 chr15: 20266959- chr15: 25099351- Del NT 3.75 1.13E−01 3 3 SNRPN** 25480660 25102073 19 15q11.2 chr15: 20266959- chr15: 25099351- Dup NT 45.19  7.93E−08 12 1 SNRPN** 25480660 25102073 20 15q11.2 chr15: 25582397- chr15: 25579767- Dup* Validated (chr15: ∞ 3.86E−06 8 0 between 25684125 25581658 25576642- SNORD109A and 25581880) UBE3A** 21 15q11.2 chr15: 25582397- chr15: 25582882- Dup* NT 30.08  2.82E−05 8 1 UBE3A** 25684125 25662988 22 16p12.2 chr16: 21901310- chr16: 21958486- Dup NT ∞ 4.47E−02 2 0 C16orf52, 22703860 22172866 UQCRC2**, PDZD9, VWA3A 23 16p11.2 chr16: 29671216- chr16: 29664753- Del NT 7.47 1.15E−01 2 1 DOC2A**, ASPHD1, 30173786 30177298 LOC440356, TBX6, LOC100271831, PRRT2 CDIPT, QPRT, YPEL3, PPP4C, MAPK3**, SPN, MVP, FAM57B, ZG16, ALDOA, INO80E, SEZ6L2, TAOK2, KCTD13, MAZ, KIF22, GDPD3, C16orf92, C16orf53, TMEM219, C16orf54, HIRIP3 24 16q23.3 chr16: 82195236- chr16: 82423855- Dup NT ∞ 4.46E−02 2 0 between 82722082 82445055 MPHOSPH6 and CDH13 25 17p12 chr17: 14139846- chr17: 14132271- Dup Validated (chr17: 1.60 3.57E−01 3 7 between COX10 and 15282723 14133349 14132271- CDRT15 14133568) 26 17p12 chr17: 14139846- chr17: 14132271- Del NT 5.61 6.70E−02 3 2 PMP22**, CDRT15, 15282723 15282708 TEKT3, MGC12916, CDRT7, HS3ST3B1 27 17p12 chr17: 14139846- chr17: 14952999- Dup NT 3.74 1.98E−01 2 2 between CDRT7 and 15282723 15053648 PMP22 28 17p12 chr17: 14139846- chr17: 15283960- Del Validated (chr17: 3.74 1.13E−01 3 3 between TEKT3 and 15282723 15287134 15283960- FAM18B2-CDRT4 15287134) 29 20p12.3 chr20: 8044044- chr20: 8162278- Dup NT 3.73 1.98E−01 2 2 PLCB1** 8527513 8313229 30 Xp21.2 chrX: 28605682- chrX: 29944502- Dup NT ∞ 4.47E−02 2 0 IL1RAPL1** 29974014 29987870 31 Xq27.2 chrX: 139998330- chrX: 140329633- Del Validated (chrX: 7.48 2.06E−02 4 2 SPANXC 140443613 140348506 140329633- 140456325) 32 Xq28 chrX: 148858522- chrX: 148882559- Del Validated (chrX: ∞ 4.46E−02 2 0 MAGEA8 149097275 148886166 148882559- 149020410) *Denotes CNVs contiguous with the chromosome 15q11.2-13.1 CNVs shown in Table 3. **Denotes gene in or adjacent to the CNV that is involved in neural function, development and disease (see Table 5-6).

Pathway Analysis.

Analysis of 104 genes within or immediately flanking our PCR-validated CNVs yielded significant association of these genes to previously characterized functional networks. The five most statistically significant networks, along with their statistical scores, are shown in Table 5. The top ranking functional categories identified in this analysis, along with their P-values, are shown in Table 6.

TABLE 5 Top Significant Networks Identified by Pathway Analysis using Ingenuity IPA. Network Score Cell-To-Cell Signaling and Interaction, Tissue 55 Development, Gene Expression Neurological Disease, Behavior, Cardiovascular Disease 28 Cell Death, Cellular Compromise, Neurological Disease 26 Cellular Development, Cell Morphology, Nervous System 20 Development and Function Behavior, Cardiovascular Disease, Neurological Disease 18 Network scores are the −log P for the results of a right-tailed Fisher's Exact Test.

As expected for CNVs associated with a neurodevelopmental disorder, a significant number of genes in or adjacent to the CNVs described here are involved in neural function, development and disease (Tables 5-6). Examples of such genes include: GABRA5, GABRA3, GABRG3, UBE3A, E2F1, PLCB1, PMP22, AADAT, MAPK3, NRXN1, NRG3, DPP10, UQCRC2, USH2A, NECAB3, CNTN4, LINGO2, IL1RAPL1, STXBP5, DOC2A, and SNRPN. Of these genes, E2F1, AADAT, NECAB3, and IL1RAPL1 are not found in the Autism Chromosome Rearrangement Database (see website at projects.tcag.ca/autism/), suggesting that they may be novel ASD risk genes.

The novel ASD risk loci identified here have functions that suggest a significant role in brain function and architecture. As such, altering the function of each of these genes as a result of the CNV could impinge on the biochemical pathways that are relevant to ASD etiology.

For example, mutations in IL1RAPL1 have been observed in cases of X-linked intellectual disability [47], and the encoded protein has been shown to play a role in voltage-gated calcium channel regulation in cultured cells [48]. E2F1 encodes a transcription factor and DNA-binding protein that plays a significant role in regulating cell growth and differentiation, apoptosis and response to DNA damage (reviewed in Biswas and Johnson, 2012 [49]). Each of these genes thus could have detrimental impacts on normal brain function.

NECAB3 encodes a neuronal protein with two isoforms that regulate the production of beta-amyloid peptide in opposite directions, depending on whether exon 9 of NECB3 is included in or excluded from the mature mRNA [50].

AADAT encodes an aminotransferase with multiple functions, one of which leads to the synthesis of kynurenic acid. This pathway has been proposed as a target for potential neuroprotective therapeutics, indicating the potential significance of this finding for ASD etiology (reviewed in Stone et al., 2012 [51]). The specific roles that any of these genes play in ASD etiology have yet to be determined, but the observed neurological functions of their encoded proteins strongly support a potential role in normal brain function.

Many of these genes also have been implicated in other nervous system disorders, including Huntington's, Parkinson's, and Alzheimer's diseases as well as schizophrenia and epilepsy [41, 52-61]. One of the features common to this group of disorders, which includes ASD, is synaptic dysfunction. There is a significant overlap in genes, and/or the molecular mechanisms by which these genes give rise to synaptopathies (reviewed in [62]). We therefore find it notable that many such genes involved in other synaptopathies were found within or flanking the validated CNVs we identified as associated with ASD.

In addition to neurogenic genes, validated CNVs were associated with genes with known roles in renal and cardiovascular diseases (Table 6). Several syndromic forms of autism, such as DiGeorge Syndrome and Charcot-Marie Tooth Disease are comorbid with renal and cardiovascular disease, and therefore it was not surprising to find that our study identified CNVs containing genes associated with these syndromes and functions, such as CDRT15, and CDH13.

TABLE 6 Top Significant Biological Functions Identified by Ingenuity IPA and Literature Searches. Function p-value range # Genes Neurological Disease 2.71E−05-3.15E−02 14 (18) Behavior 5.93E−05-4.36E−02 10 Cardiovascular Disease 8.58E−05-4.30E−02 10 Cellular Development 1.39E−04-4.77E−02 9 Inflammatory response 4.84E−04-2.89E−02 6 The right-tailed Fisher's exact test was used to calculate P-values representing the probability that selecting genes associated with that pathway or network is due to chance alone. Each functional category represents a collection of associated subcategories, each of which has an associated P-value. For example, within ‘Neurological Disease,’ are subcategories of genes associated with seizures, Huntington Disease, schizophrenia, etc. The P-value range range given represents the range of P-values generated for each subcategory. In the first line, 36 genes were associated with a function in Neurological Disease by Ingenuity software. An additional 11 genes were identified as having neurological functions in the literature, giving a total of 47 with known or suspected roles in neurological disease.

There is mounting evidence, as well, that inflammatory responses are involved with the development and progression of autism (reviewed in [63]). Maternal immune activation during pregnancy is believed to activate fetal inflammatory responses, in some cases with detrimental effects on neural development in the fetus, leading to autism. This environmental insult could be mediated or enhanced by genomic changes that predispose the fetus to elevated inflammatory responses, so it is significant that a number of genes from our validated CNVs play a role in inflammatory response. Examples of these include CD160, CALCR, and SPN.

These findings are consistent with other studies that used pathway analysis to characterize the genes contained in ASD risk CNVs, and suggest that many different biological pathways, when disrupted, can lead to features observed in ASD. The wide variety of biological functions identified for these genes also is consistent with estimates of the number of independent genetic variants that may play a role in the etiology of ASD (8-11).

A custom microarray was used to characterize the frequency of CNVs identified in high-risk ASD families in a large ASD case/control population. We also evaluated further the frequency of CNVs discovered in several published studies in our sample cohort to obtain a clearer picture of the potential clinical utility of these CNVs in the genetic evaluation of children with ASD. Multiple quality control measures were used to insure that all cases and controls a) had no unexpected familial relationships; b) represented a uniform ethnic group; c) were devoid of uncharacterized whole chromosome anomalies or other genomic abnormalities consistent with syndromic forms of ASD; d) had sufficient power to distinguish risk variants from CNVs with little or no impact on the ASD phenotype; and e) were validated using quantitative PCR even though the custom array used here represented at least a second evaluation for most of them. Parents of ASD cases tested were not available to determine state of inheritance.

The validity of this approach was confirmed by our observation of CNVs that had been previously identified as ASD risked markers, including CNVs encompassing parts of the NRXN1 gene. CNVs and point mutations in NRXN1 are thought to play a role in a subset of ASD cases as well as in other neuropsychiatric conditions [15, 32, 36-40]. The data from our study demonstrate that NRXN1 CNVs also occur in high-risk ASD families. Further, our case/control data provide additional evidence that neurexin-1 plays an important role in unrelated ASD cases. While CNVs near NRXN1 occur in controls as well as in cases, the CVNs observed in our ASD cases typically disrupt a portion of the NRXN1 coding region while CNVs observed in our control population do not.

CNVs from High-Risk ASD Families.

In the high-risk ASD families, both novel and previously observed CNVs were identified that contain genes with potential relevance to neuropsychiatric conditions such as ASD. These include CNVs involving LINGO2, the GABR gene cluster on chromosome 15q12 and STXBP5. Each of these CNV regions has an odds ratio greater than 2 and most of the CNVs we identified in high-risk families have a significant p value associating them with the ASD phenotype in this case/control study. Some CNVs, although observed only in ASD cases and not in controls, were too rare even in this large dataset to generate statistically significant results. An example is a deletion involving STXBP5 that was observed two ASD samples and in no controls. A deletion including this gene was previously observed in a patient with an apparent syndromic form of ASD [64], lending further support to our observation of STXBP5 deletions in ASD cases. These data collectively suggest that CNVs observed in high-risk ASD families also are important contributors to the etiology of ASD in an ASD case/control population.

Rare duplications involving the GABA receptor gene cluster as well as additional genes in the Prader-Willi/Angelman syndrome region on chromosome 15 were detected (11/1,544 unrelated cases, 1/5,762 unrelated controls, OR=40.05). All of these CNVs were confirmed using TaqMan assays spanning the region, and these results strongly suggest a role for duplications on chromosome 15q12 in ASD etiology. Deficiency of GABA_(A) receptors indeed is thought to play an important role in both autism and epilepsy, and duplications have been observed to result in decreased GABR expression through a potential epigenetic mechanism (reviewed in [65]). Further, differences in the expression of GABRB3 mRNA and protein in the brains of some children with autism have been reported along with loss of biallelic expression of the chromosome 15q GABR genes in some individuals, [66], suggesting that epigenetic regulation of the chromosome 15 GABR gene cluster could also contribute to ASD etiology. Consistent with many previous findings from family studies, case reports and modest case/control studies (see website at omim.org/entry/608636), our data provide additional support for the involvement of duplications in this region of the genome in ASD. Further, the large population study suggests that these duplications may explain as much as 0.7% of ASD cases.

A recent study searching for CNVs encompassing genes in the GABA pathway, including the chromosome 15 GABR gene cluster, also found CNVs in this region. In contrast to our findings, this study found GABR gene cluster duplications at similar frequencies in both cases and in controls (Table S2 in ref. [44]). In addition, deletions were more common in this study in both cases and controls, while duplications were more common in our data. The differences between the two studies may lie in the sample population being studied, the uniformity of our sample population, or the technology platform used for CNV discovery (custom Illumina array compared to a custom Agilent array). Previous results have demonstrated maternal inheritance of deletions in this region in children with autism [67]. However, in our family studies we did not observe CNVs involving chromosome 15q12, and our case/control data preclude us from determining the parent of origin.

Interestingly, the CNVs that we observed on chromosome 15q were detected primarily with probes for SNVs identified in the GABR genes. Further, these SNVs were identified in affected individuals from high-risk ASD families. We did not observe CNVs involving this region in our high-risk ASD families. The observation of frequent duplications in our case/control population in the region containing these genes, coupled with the detection of these CNVs using probes for potential detrimental single nucleotide variants, suggests that both SNVs and CNVs involving the GABR genes might be pathogenic.

Literature Supported CNVs.

In addition to the CNVs identified in our high-risk ASD families, we evaluated further ASD risk CNVs identified in previous studies. Our results (Table 4) clearly demonstrate a role for many of these CNVs in ASD pathogenesis. Consistent with previous results, our data demonstrate in a large ASD population that rare CNVs are likely to play a role in the genetics of ASD, and suggest that these CNVs should be included in the Genetic evaluation of children with ASD.

Interestingly, recent publications have identified a recurrent duplication of the Williams syndrome region on chromosome 7q11.23 in children with ASD [9,11]. We included probes for this region on our custom array, and were not able to identify any 7q11.23 duplications in our datasets. The reason(s) we did not observe any duplications in this region is not obvious; we had adequate probe coverage to have seen such duplications if they were present. Similar to the simplex ASD families used in those published studies, most of our ASD samples also were from reported simplex families, so the lack of observation of these CNVs is unlikely to be due to differences in family structure.

A CNV discovered at CHOP and not previously published includes a portion of the LCE gene cluster on chromosome 1. Deletions in this region have been associated with psoriasis [68,69], but no variants in this region have been linked to autism. Focusing solely on individuals of Caucasian ancestry, we observed this CNV deletion in a single case and also a single control. However, when we included samples of non-Caucasian or uncertain ancestry, we observed 27 additional case DNA samples that carried this deletion, while only a single additional CNV-positive control was observed. Based on SNP genotype results from principal component analysis, all of the cases that were positive for this CNV were of Asian descent. Since our control cohort had few individuals of Asian descent, we suspected that this CNV might be common in the Asian population. Analysis of whole genome data for individuals of non-Caucasian ancestry genotyped at the Center for Applied Genomics did not demonstrate common CNVs in either cases or controls in this region in individuals with Asian ancestry. However, a common CNV including LCE3E was observed in individuals with African ancestry (unpublished observations). Further analysis will be necessary to determine if this CNV is an ASD risk variant in either Asian or African populations.

Effect of Analysis Method on CNV Validation.

Although some CNVs are described here for the first time, many of the CNVs that we evaluated in this study were described previously. It is interesting to note that individual CNV calls that were made with both of the software packages we used were much more likely to be validated by qPCR than were CNVs called by either program alone. In fact, 97% of the CNVs called by both PennCNV and CNAM validated using TaqMan qPCR assays, while only 24% of the CNVs called by PennCNV alone and 30% of the CNVs called by CNAM alone were validated using the same approach. The concordance between the two analysis methods is informative given that the final sample sets used by the two methods differed substantially. The CNAM analysis used 290 fewer case samples and 575 fewer control samples than the PennCNV analysis. These data clearly demonstrate the value of using multiple software packages to evaluate microarray data for CNV discovery work. Our data are consistent with the rarity of many CNVs detected in DNA from children with ASD, and with the suggestion that there may be hundreds of loci that contribute to the development of ASD [9,11].

These data demonstrate that CNVs identified in high-risk ASD families play a role in the etiology of ASD in unrelated cases. Evaluation of these CNVs in the large sample set used in this study provides compelling evidence for extremely rare recurrent CNVs as well as additional common variants in the genetics of ASD. We suggest that the CNVs described here likely have a strong impact on the development of ASD. Given the extensive quality control measures used to characterize the sample cohort, the frequency at which we observed these CNVs in our cohort, and the molecular validation that we used to verify the calls, these CNVs can be used to increase sensitivity in the genetic evaluation of children with ASD. Further work will help to determine if the CNVs reported here are important for specific clinical subsets of ASD cases.

Samples:

All high risk ASD family members and controls were of self-reported European ancestry. Among all cases in the replication study, 84% were of self-reported European ancestry, 6% were of self-reported African ancestry, 5% were self-reported as having multiple ethnic origins, and 5% were of unknown ethnicity. Among the cases, 1,577 were reported from unique families, 864 from 432 different families with 2 siblings, 369 from 123 different families with 3 siblings, 172 from 43 different families of 4 siblings, 5 siblings from a single family, 6 siblings from a single family, and 7 siblings from a single family. Among the DNA from cases used for genotyping, 1% came from cell pellets, 61% come from lymphoblastoid cell lines, 35% came from whole blood, and for 3% the source of DNA remained unknown. DNA was extracted from cell lines or lymphocytes, and quantitated using UV spectrophotometry. Six thousand controls were recruited by CHOP after obtaining informed consent under an IRB approved protocol. All DNA samples from controls were extracted from whole blood. Only individuals with self-reported Caucasian ancestry were used for this study. Pairwise identity by descent (IBD) was used to confirm known family assignments for cases, and to identify cryptic relatedness arising out of multiple subject enrollments across/within cohorts for all samples. Related individuals were removed so that only one family member remained in the study.

Array Processing:

We used 250 ng of genomic DNA to genotype each sample, according to the manufacturer's guidelines. On day one, genomic DNA was amplified 1000-1500-fold. Day two, amplified DNA was fragmented ˜300-600 bp, then precipitated and resuspended, followed by hybridization on to a BeadChip. Single base extension (SBE) utilizes a single probe sequence ˜50 bp long designed to hybridize immediately adjacent to the SNP query site. Following targeted hybridization to the bead array, the arrayed SNP locus-specific primers (attached to beads) were extended with a single hapten-labeled dideoxynucleotide in the SBE reaction. The haptens were subsequently detected by a multi-layer immunohistochemical sandwich assay, as recently described (Pastinen et al., 2000, Genome Res. 10, 1031, Erdogan et al., 2001, Nuc. Acids Res. 29, E36). The Illumina iScan was used to scan each BeadChip at two wavelengths and an image file was created. As BeadChip images were collected, intensity values were determined for all instances of each bead type, and data files were created that summarized intensity values for each bead type. These files were loaded directly into Illumina's genotype analysis software, BeadStudio. A bead pool manifest created from the LIMS database containing all the BeadChip data was loaded into BeadStudio along with the intensity data for the samples. BeadStudio used a normalization algorithm to minimize BeadChip to BeadChip variability. Once the normalization was complete, the clustering algorithm was run to evaluate cluster positions for each locus and assign individual genotypes. Each locus was given an overall score based on the quality of the clustering and each individual genotype call was given a GenCall score. GenCall scores provided a quality metric that ranges from 0 to 1 assigned to every genotype called. GenCall scores were then calculated using information from the clustering of the samples. The location of each genotype relative to its assigned cluster determined its GenCall score.

Sample Quality Control:

Quality control measures were intended to identify the samples with the greatest probability of successful CNV identification and to remove the samples with features making CNV identification problematic. Most of the QC metrics employed were originally designed for applications involving high-density genome-wide data. For this study, it was deemed possible that an otherwise high-quality sample with a few large CNVs might fail some QC metrics due to the sparse nature of the data from the custom array employed. The QC process was therefore approached with caution, and inclusion criteria were determined by manual review of the data for each metric in order to identify the outlier values.

Derivative Log Ratio Spread (DLRS):

Derivative Log Ratio Spread (DLRS) is a measurement of point-to-point consistency of LR data, and is a reflection of the signal-to-noise ratio. It is similar in nature to the standard deviation of LR values that is often used in CNV studies, but has the advantage of being robust against large CNVs, which may influence standard deviation. DLRS was calculated for each chromosome, and the median chromosome DLRS value was used as a quality test. The distribution of the median DLRS statistic can be seen below. The outlier threshold was set at 0.3. One hundred twenty-eight subjects fail at this threshold, including all of the 75 samples that failed the waviness factor QC metric (see below).

Waviness Factor:

The “waviness” of each sample in the study was measured using the method of Diskin, et al. [27] as employed within SVS. An absolute value of 0.2 was determined as the outlier threshold for this metric, and 75 subjects failed at this threshold.

Chromosomal Abnormalities and Cell-Line Artifacts:

Fifty-one samples (12 cases and 39 controls) were determined to have a chromosome 21 trisomy, consistent with a diagnosis of Down syndrome. These subjects were later confirmed to have Down syndrome based on clinical data review, and were removed from all further analyses. Additionally, 10 samples were removed based on other abnormalities that appeared to affect entire chromosomes.

Excessive CNVs:

During the course of our analysis, several subjects were noted, using heat map style plots, to have a high frequency of copy number variant regions, in particular copy number gains. To identify the problematic subjects, we estimated the proportion of autosomal CNV regions in the data for which each subject had any CNV gain or loss. After manual review of the distribution of this proportion, 17 subjects with CNV calls at more than 10% of the regions were dropped from further analysis.

Principle Component Analysis (PCA).

Substantial stratification was observed in the LR intensity data. The first two components were stratified by gender, and additional stratification and clustering was observed in the higher components as well. It was therefore considered prudent to apply a PCA correction to the intensity data prior to analysis in order to reduce the probability of data artifacts influencing CNV calls. The principal components were calculated based on all 9,000 samples in the QC process and the results were skewed by the presence of low quality samples. The principle components were therefore recalculated for the 8,777 samples passing preliminary QC, including samples that passed the tests for waviness, DLRS, PCA outliers, chromosome 21 trisomies, and the initial genotyping lab QC. After calculating the first 50 principal components and examining the distribution of eigenvalues, the LR values were corrected for 20 principal components, which were determined to be sufficient to explain the majority of variability in the data. The corrected LR data was then used for segmentation and CNV identification.

CNV Calling:

The segmentation covariates were reduced to a non-redundant spreadsheet, with columns for each marker position where at least one subject had an intensity shift. The distribution of values for each of these columns then was analyzed to determine if multiple copy number states were present, and if so, to estimate the threshold values that defined the different classes. The threshold values were first estimated by a simple algorithm that identified the mode of the distribution, and assuming this to be the neutral copy number state, set upper and lower thresholds based on the variance of the distribution. These thresholds were then manually reviewed, and gross errors were corrected as necessary. After threshold values were confirmed for each of the non-redundant regions, each subject's data for that region was classified accordingly as loss, gain, or neutral. These values were then used to populate a table of discrete copy number calls for use in association testing.

TaqMan Assays:

DNA samples and controls were transferred from stock tubes and diluted with molecular grade water to a final concentration of 5 ng/ul into 0.75 mL Thermo Scientific Matrix storage tubes. All pipetting steps were carried out using Beckman Coulter Biomek FXp automation (Beckman Coulter, Inc., Fullerton, Calif., USA) unless otherwise stated. For each assay, 14 ul of each sample were plated into rows of a 96-well full-skirted plate. The last well in each row was left blank as a non-template control. Each quadrant of the 384-well reaction plates was stamped with 2 ul of DNA from the 96-well sample plate, so that each sample was assayed in quadruplicate. The reaction plates were dried and stored at 4° C. The TaqMan® reaction mix for each assay was prepared according to Applied Biosystems' (Applied Biosystems, Foster City, Calif., USA) recommendations with RNaseP as the reference assay (reference gene) and transferred by hand to each row of a 96-well full-skirted plate. 10 uL of each assay mix was then stamped into the appropriate reaction plate containing 10 ng of dried down DNA per well. The reaction plates were sealed with optical adhesive film, mixed on a plate vortex mixer, and centrifuged prior to running on the Applied Biosystems 7900HT Real Time PCR instrument. Thermal cycling was performed according to the manufacturer's recommended protocol (Applied Biosystems. Data were analyzed with SDS v2.4 software (Applied Biosystems). The baseline was calculated automatically and the threshold was set manually based on the exponential phase of the amplification plot. Data were exported as a text file and imported into the Applied Biosystems CopyCaller v2.0 Program. Assays were analyzed by setting a negative control sample (selected from samples showing none of the CNVs under study by either PennCNV or CNAM) copy number to n=2 except for X chromosome assays, which were analyzed using n=1. For X chromosome CNVs both male and female control samples were used (3 male, 2 female). All other parameters were left as default.

Pathway Analysis.

Ninety of the genes analyzed were within CNV duplications and 63 genes were within CNV deletions. Eighty-seven genes were included since they were the gene nearest to a validated intergenic CNV. Gene abbreviations were batch converted to their Entrez Gene IDs using G:CONVERT [31,32]. Both DAVID and Ingenuity IPA use the right-tailed Fisher's Exact test to calculate P-values representing the probability that selecting genes associated with that pathway or network is due to chance alone.

Network Generation Using IPA:

Each gene in our list of 240 was mapped to its corresponding object in Ingenuity's Knowledge Base. These genes were overlaid onto a global molecular network developed from information contained in Ingenuity's Knowledge Base. Networks then were algorithmically generated based on their connectivity. Both direct and indirect interactions were searched. Network scores are the −log P for the results of a right-tailed Fisher's Exact Test.

Principle Component Analysis (PCA) Results.

Principal components analysis was used to assess the impact of population stratification within the study subjects. Principal components were calculated in SVS using default settings. All subjects were included in the calculation except those that failed data QC. Prior to calculating principal components, the SNPs were filtered so that only SNPs that met the following criteria were used: 1) autosomal SNPs only; 2) call rate>0.95; 3) MAF>0.05; 4) linkage disequilibrium R²<25% for all pairs of SNPs within a moving window of 50 SNPs. In total 2008 SNPs met these criteria. Self-reported ethnicity was used to group samples into “Caucasian” and “non-Caucasian” sets. A simple outlier detection algorithm was applied to stratify the subjects into the two groups. This was done by first calculating the Cartesian distance of each subject from the median centroid of the first two principal component vectors. After determining the third quartile (Q3) and inter-quartile range (IQR) of the distances, any subject with a distance exceeding Q3+1.5*IQR was determined to be outside of the main cluster, and therefore non-Caucasian. Five hundred sixty-four subjects were placed in the non-Caucasian category, including 207 cases and 57 controls. A small number of samples were removed due to duplicate enrollment in the study, but no other unexpected relationships were identified.

TABLE 7 TaqMan Assays Used for CNV Validation Start Coord. End Coord. Chromosome (hg19) (hg19) Assay Name chr1 145608130 145608131 Hs01960835_cn chr1 145714157 145714158 Hs03356306 chr1 145727743 145727744 Hs02151880 chr1 145831706 145831707 Hs03363224_cn chr1 215857628 215857629 Hs06533545_cn chr1 215860518 215860519 Hs05788384_cn chr2 13206303 13206304 Hs05832292_cn chr2 51257082 51257083 Hs04675592_cn chr2 51273782 51273783 Hs03406712_cn chr2 51335043 51335044 Hs03207855_cn chr2 78417269 78417270 Hs03210777 chr2 78448009 78448010 Hs03219183 chr3 1940242 1940243 Hs03449476_cn chr3 74559838 74559839 Hs06657187_cn chr3 74570239 74570240 Hs03006662_cn chr3 74580064 74580065 Hs06656853_cn chr3 172593661 172593662 Hs05888850_cn chr3 172600469 172600470 Hs04760981_cn chr3 174853869 174853870 Hs03492315_cn chr3 174889051 174889052 Hs03463132_cn chr3 176765106 176765107 Hs00705847 chr3 176773900 176773901 Hs06653638 chr3 178962631 178962632 Hs04718548_cn chr3 178969356 178969357 Hs00989875_cn chr4 73785471 73785472 Hs04844255_cn chr4 73923259 73923260 Hs02916212_cn chr4 74027025 74027026 Hs00308217_cn chr4 189089063 189089064 Hs03238737 chr4 189109145 189109146 Hs03244159 chr5 99647650 99647651 Hs03245981_cn chr5 99665469 99665470 Hs03248003_cn chr5 118544341 118544342 Hs06046822_cn chr5 118567989 118567990 Hs03578408_cn chr5 118606921 118606922 Hs03562094_cn chr6 7464166 7464167 Hs03258806_cn chr6 7467367 7467368 Hs03261355_cn chr6 39070306 39070307 Hs06797005_cn chr6 44131202 44131203 Hs06765368_cn chr6 49257472 49257473 Hs06135362_cn chr6 62432331 62432332 Hs06740361_cn chr6 62468865 62468866 Hs06752297_cn chr6 127449047 127449048 Hs04898996 chr6 127467261 127467262 Hs06149095 chr6 147599263 147599264 Hs00462911_cn chr6 147649513 147649514 Hs06799063_cn chr6 147681914 147681915 Hs04903013_cn chr7 6870706 6870707 Hs03632408_cn chr7 15383278 15383279 CusTaq1CX6RM14_cn chr7 15405201 15405202 ContR26CX0IV8W_cn chr7 93080844 93080845 Hs04974410_cn chr7 93145475 93145476 Hs04971099_cn chr7 93152478 93152479 Hs04944233_cn chr7 100232257 100232258 Hs03629609 chr7 100304948 100304949 Hs01981045 chr7 100381692 100381693 Hs05013769 chr7 124527535 124527536 Hs03620793_cn chr7 124578724 124578725 Hs03650226_cn chr7 149504056 149504057 Hs03630536 chr7 149528561 149528562 Hs03645125 chr7 149550437 149550438 Hs03640597 chr8 3165293 3165294 Hs02622320_cn chr8 54865516 54865517 Hs03668894_cn chr8 54905347 54905348 Hs03694907_cn chr8 84323860 84323861 Hs04360657 chr8 84331501 84331502 Hs03658852 chr8 85298919 85298920 Hs03668441_cn chr8 85303238 85303239 Hs03678663_cn chr8 86467253 86467254 Hs03673176_cn chr9 28203352 28203353 Hs03707922_cn chr9 28266812 28266813 Hs03714527_cn chr9 28333835 28333836 Hs03725541_cn chr9 28354528 28354529 Hs03723870_cn chr9 136523906 136523907 Hs01617069_cn chr9 136527743 136527744 Hs06869845_cn chr9 139091261 139091262 Hs06889516_cn chr9 139101729 139101730 Hs06847090 chr9 139110612 139110613 Hs00495475 chr10 83887149 83887150 Hs03726621_cn chr10 89717970 89717971 Hs05212456 chr10 92274027 92274028 Hs03746257 chr10 92287873 92287874 Hs03740287 chr12 53178157 53178158 Hs06965067_cn chr12 53181253 53181254 Hs06930722_cn chr12 71934616 71934617 Hs06933395_cn chr12 71950419 71950420 Hs01107784_cn chr12 73071721 73071722 Hs06996317_cn chr12 73094916 73094917 Hs03093848_cn chr12 80898972 80898973 Hs03825941_cn chr12 80974071 80974072 Hs03820308_cn chr12 81007496 81007497 Hs03818167_cn chr12 81610738 81610739 Hs00229436_cn chr12 81693094 81693095 Hs00586334_cn chr12 81746602 81746603 Hs06985491_cn chr12 102097529 102097530 Hs06981209_cn chr12 102105668 102105669 Hs04412303_cn chr13 40089549 40089550 Hs03853267_cn chr13 93444276 93444277 Hs04432382 chr13 93460071 93460072 Hs04432043 chr14 24519089 24519090 Hs03883350 chr14 24534221 24534222 Hs01939905 chr14 28522635 28522636 CusTaq2CXLJH4P_cn chr14 37916895 37916896 Hs07055190_cn chr14 37977977 37977978 Hs07044926_cn chr14 38014166 38014167 Hs07086625_cn chr14 38021288 38021289 Hs07075472_cn chr14 96763309 96763310 Hs05318569_cn chr14 96772014 96772015 Hs00982344_cn chr14 99641385 99641386 Hs00596122_cn chr14 100734909 100734910 Hs03875129 chr14 100765197 100765198 Hs01931607 chr14 100795059 100795060 Hs00201515 chr14 101000582 101000583 Hs03874127_cn chr14 101005643 101005644 Hs01983727_cn chr14 102021598 102021599 Hs03877829_cn chr14 102025461 102025462 Hs03890390_cn chr14 102737644 102737645 Hs04443274_cn chr14 102744822 102744823 Hs04436664_cn chr14 102974514 102974515 Hs03874565_cn chr14 104035624 104035625 Hs07076467 chr14 104089093 104089094 Hs07094555 chr14 104134199 104134200 Hs07101222 chr15 20194087 20194088 Hs04444017 chr15 25578159 25578160 Hs03899505_cn chr15 25580751 25580752 CusTaq3CX20SJR_cn chr15 25739587 25739588 Hs03895201_cn chr15 26170697 26170698 Hs03899220_cn chr15 26218978 26218979 Hs07535627_cn chr15 26566910 26566911 Hs05379477_cn chr15 26758634 26758635 Hs05357961_cn chr15 27186676 27186677 Hs05354636_cn chr15 27215751 27215752 Hs05352889_cn chr15 28430324 28430325 Hs03904620_cn chr15 28464592 28464593 Hs03900299_cn chr15 28510861 28510862 Hs00790698_cn chr15 30008107 30008108 Hs03905821_cn chr15 30028029 30028030 Hs03894282_cn chr15 31233791 31233792 Hs01761674_cn chr15 31418708 31418709 Hs03907602_cn chr15 31523604 31523605 Hs05345027_cn chr15 31779480 31779481 Hs01740084_cn chr15 31792000 31792001 Hs03903842 chr15 31807369 31807370 Hs03898720 chr15 31819397 31819398 Hs01183107_cn chr15 40565562 40565563 Hs01801490_cn chr15 40569495 40569496 Hs03050146_cn chr15 40574016 40574017 Hs03915257 chr15 40600033 40600034 Hs02747689 chr15 40631492 40631493 Hs05348776 chr15 42140352 42140353 Hs01736986_cn chr15 42220283 42220284 Hs05327333_cn chr15 42278083 42278084 Hs07457532_cn chr15 56246674 56246675 Hs05388304_cn chr15 56258673 56258674 Hs02776763_cn chr16 2137638 2137639 Hs03948922_cn chr16 2139578 2139579 Hs01690407_cn chr16 83908973 83908974 Hs03924139_cn chr16 83927884 83927885 Hs03920294_cn chr17 14133533 14133534 Hs05489546_cn chr17 15285417 15285418 Hs05479141_cn chr19 23823676 23823677 Hs07158898_cn chr19 23847358 23847359 Hs07130588_cn chr19 43260846 43260847 Hs04483050_cn chr19 52919934 52919935 Hs01762991_cn chr19 52961357 52961358 Hs04015789_cn chr20 8654182 8654183 Hs07182273_cn chr20 8655323 8655324 Hs07214628_cn chr20 8656129 8656130 Hs07196671 chr20 8662295 8662296 Hs07181996 chr20 32267585 32267586 Hs03035919 chr20 32324773 32324774 Hs04040566 chr20 32380921 32380922 Hs07167677 chr20 35244629 35244630 Hs07189989_cn chr20 35286976 35286977 Hs07187468 chr20 35339976 35339977 Hs07195828 chr20 35392781 35392782 Hs07216584 chr20 57246270 57246271 Hs00451592_cn chr20 57276159 57276160 Hs02247879_cn chr20 57283659 57283660 Hs07195366_cn chrX 140316814 140316815 Hs04119700_cn chrX 140348402 140348403 Hs04105155_cn chrX 140394910 140394911 Hs04123806_cn chrX 140450224 140450225 Hs04514589_cn chrX 140560608 140560609 Hs04117605_cn chrX 140711967 140711968 Hs04108237 chrX 140730389 140730390 Hs04114029 chrX 147283785 147283786 Hs05619718 chrX 147557625 147557626 Hs05666138 chrX 147831902 147831903 Hs05592380 chrX 148101715 148101716 Hs05606186 chrX 148379988 148379989 Hs05667154 chrX 148892085 148892086 Hs04109160_cn chrX 148999489 148999490 Hs04513800_cn chrX 149014384 149014385 Hs02798232_cn chrX 153195418 153195419 Hs02879994_cn chrX 153200970 153200971 Hs01730847_cn

TABLE 8 153 CNVs in subjects with autism in Utah families Custom iSelect ACRD Gain/ Array No. Chrom Start (hg19) End (hg19) Published? Ref. No. Loss Size (bp) Gene Probes  1 chr1 4737693 4746636 N Loss 8943 AJAP1 20  2 chr1 10624023 10627542 N Loss 3519 PEX14 14  3 chr1 145714421 146101228 N Gain 386807 more than 10 genes 20  4 chr1 169704308 169732211 N Loss 27903 C1orf112 20  5 chr1 179456385 179472635 N Loss 16250 C1orf125/DKFZp434N1720 20  6 chr1 204193679 204209979 N Loss 16300 PLEKHA6 20  7 chr1 215858193 215861879 Y 4 Loss 3686 USH2A 19  8 chr1 225508461 225511454 N Loss 2993 DNAH14 14  9 chr1 228848896 228853665 N Loss 4769 5′ of RHOU 11 10 chr1 237993724 237995299 N Loss 1575 RYR2 15 11 chr1 243860912 243861049 N Loss 137 AKT3 10 12 chr2 12685369 12693172 N Loss 7803 AK001558 16 13 chr2 32982548 33050816 Y 2, 5 Gain 68268 TTC27, AK095182 15 14 chr2 37904904 37909117 N Gain 4213 5′ of CDC42EP3 19 15 chr2 45997209 45997519 N Loss 310 PRKCE 11  16* chr2 51272055 51336043 Y 2, 4 Loss 63988 5′ of NRXN1 (10 kb) 83 17 chr2 52420563 52584090 N Loss 163527 5′ of NRXN1 (1 Mb) 20 18 chr2 58346718 58349248 Y 2 Loss 2530 VRK2 12 19 chr2 62195814 62230970 N Loss 35156 COMMD1, CR603473 20 20 chr2 75014711 75044204 N Loss 29493 5′ of HK2 20 21 chr2 79330766 79342811 N Gain 12045 5′ of REG1B, 5′ of 17 REG1A 22 chr2 120130796 120145728 N Loss 14932 5′ of C2orf76, 5′ of 20 TMEM37 23 chr2 236424336 236465062 N Loss 40726 AGAP1 20 24 chr3 6724453 7046515 N Gain 322062 AF279782, GRM7 20 25 chr3 12387768 12393125 N Loss 5357 PPARG 20  26* chr3 21731567 21734331 N Gain 2764 ZNF385D 14 27 chr3 57051604 57053353 N Gain 1749 ARHGEF3 13 28 chr3 60774451 60777932 Y 3 Gain 3481 FHIT 16 29 chr3 63962828 63964474 N Loss 1646 ATXN7 13 30 chr3 74566042 74584605 N Loss 18563 CNTN3 20 31 chr3 171090367 171092891 N Gain 2524 TNIK 16 32 chr3 172596081 172617355 N Gain 21274 SPATA16 20 33 chr4 58811798 58816810 N Loss 5012 3′ of BC034799 (480 kb) 14 34 chr4 80865807 80887173 N Loss 21366 ANTXR2/DKFZp667K1925 17 35 chr4 101551216 101616281 N Loss 65065 5′ of EMCN (200 kb) 20 36 chr4 134924034 135188390 N Loss 264356 PABPC4L 20 37 chr4 185734577 185740215 N Loss 5638 ACSL1 18 38 chr4 189084983 189117429 N Loss 32446 3′ of TRIML1 20 39 chr5 20436884 20449034 N Loss 12150 CDH18 20 40 chr5 58469036 58470270 N Loss 1234 PDE4D 12 41 chr5 99634772 99682698 N Loss 47926 5′ of FAM174A (190 kb) 20 42 chr5 132621489 132630849 Y 2, 4 Gain 9360 FSTL4 20 43 chr5 142599442 142602063 N Loss 2621 ARHGAP26/KIAA0621 14 44 chr5 151582812 151583410 N Loss 598 AK001582 12 45 chr6 7425246 7464367 N Gain 39121 3′ of RIOK1 20 46 chr6 10856101 10872458 N Loss 16357 3′ of TMEM14B and 20 GCM2, 5′ of MAK and SYCP2L 47 chr6 42126761 42128299 N Loss 1538 GUCA1A 16 48 chr6 44113916 44180221 N Loss 66305 CAPN11, TMEM63B 20 49 chr6 47864831 49244526 N Loss 1379695 C6orf138 25 50 chr6 53856580 53864523 N Loss 7943 AK056584 19 51 chr6 62443739 62462295 N Loss 18556 KHDRBS2 17 52 chr6 119419595 119427038 Y 2 Loss 7443 FAM184A 18 53 chr6 123893763 123897553 N Loss 3790 TRDN 14 54 chr6 139985775 140128887 N Gain 143112 BC039503 20 55 chr6 147588752 147664671 Y 2 Gain 75919 STXBP5 20 56 chr6 161189018 161218651 N Loss 29633 3′ of PLG 20 57 chr7 6838712 6864071 N Loss 25359 C7orf28B 15 58 chr7 11782637 11783917 Y 4 Loss 1280 THSD7A 12 59 chr7 13962113 13962620 Y 2 Loss 507 ETV1 11 60 chr7 71597328 71603027 N Gain 5699 CALM 14 61 chr7 105285949 105321353 N Loss 35404 ATXN7L1 20 62 chr7 124546250 124580202 Y 4 Loss 33952 POT1, hypothetical proteins 20 63 chr8 3160739 3160885 N Loss 146 CSMD1/KIAA1890 10 64 chr8 3169351 3169808 N Loss 457 CSMD1/KIAA1890 11 65 chr8 3479586 3480400 N Loss 814 CSMD1 12 66 chr8 4907673 4911422 N Loss 3749 5′ of CSMD1 60 kb) 20 67 chr8 31977229 31989597 N Loss 12368 NRG1 20 68 chr8 52261992 52265315 N Loss 3323 PXDNL 15 69 chr8 84323466 84337983 N Loss 14517 3′ of BC038578 20 70 chr8 85281895 85304198 N Loss 22303 RALYL 20 71 chr8 86471729 86553130 N Gain 81401 3′ of REXO1L1 20 72 chr8 100402969 100406592 N Loss 3623 VPS13B 10 73 chr9 7036350 7051859 N Loss 15509 JMJD2C 20 74 chr9 28027694 28039222 N Gain 11528 LINGO2 20 75 chr9 28190069 28347679 N Loss 157610 LINGO2 20 76 chr9 75206337 75207666 N Gain 1329 TMC1 11 77 chr9 116468123 116631674 N Gain 163551 5′ of ZNF618 (5 kb) 12 78 chr9 139083019 139113146 N Gain 30127 LHX3, QSOX2 20 79 chr10 27361202 27381349 N Loss 20147 ANKRD26 20 80 chr10 33217225 33222978 N Loss 5753 ITGB1 11 81 chr10 38914665 42953131 N Loss 4038466 AK131313, BC039000 20 82 chr10 52133698 52232708 Y 3 Gain 99010 SGMS1/SMS1 20 83 chr10 60793303 60857532 Y 3 Gain 64229 5′ of PHYHIPL (80 kb) 20 84 chr10 68350062 68375800 N Loss 25738 CTNNA3 20 85 chr10 81032555 81037800 N Loss 5245 ZMIZ1 14 86 chr10 83893626 84175018 N Loss 281392 NRG3 13 87 chr10 86939018 86970632 N Loss 31614 AK097624 20 88 chr10 89720106 89723874 N Loss 3768 PTEN 12 89 chr10 91210650 91217984 N Loss 7334 SLC16A12 19 90 chr10 92274764 92289762 Y 2 Loss 14998 3′ of BC037970 15 91 chr11 7488341 7489819 N Gain 1478 SYT9, AK128569 16 92 chr11 12002139 12007077 N Gain 4938 DKK3 20 93 chr11 12374189 12374712 N Loss 523 MICALCL 11 94 chr11 16569019 16576640 N Loss 7621 SOX6/DKFZp434N1217 12 95 chr11 31000774 31000929 N Gain 155 DCDC5/KIAA1493 10 96 chr11 60228735 60229382 N Loss 647 MS4A1 11 97 chr11 98148399 98212796 N Gain 64397 5′ of CNTN5 (700 kb) 20 98 chr11 100817655 100820663 N Loss 3008 FLJ32810 14 99 chr11 131405729 131406206 N Gain 477 NTM, AK128059 11 100  chr12 60173356 60173878 Y 4 Gain 522 SLC16A7/MCT2 13 101  chr12 73062598 73088289 Y 2 Loss 25691 3′ of TRHDE 20 102  chr12 75547922 75572356 N Loss 24434 KCNC2 20 103  chr12 80880491 80895554 N Loss 15063 PTPRQ 20 104  chr12 80988331 81019079 N Loss 30748 PTPRQ 20 105  chr12 81618586 81626675 N Loss 8089 ACSS3 17 106  chr12 97870273 97875696 N Loss 5423 NCRMS/AK056164 20 107  chr12 102097012 102106306 N Loss 9294 CHPT1 13 108  chr12 127308503 127315005 Y, small 4 Loss 6502 between BC069215 19 overlap and BC037858 109  chr13 40087689 40088007 N Loss 318 LHFP 12 110  chr13 49284461 49343043 N Gain 58582 3′ of CYSLTR2 20 111  chr13 50163809 50179454 N Loss 15645 5′ of RCBTB1 17 112  chr13 93448487 93461603 N Loss 13116 GPC5 17 113  chr13 94357235 94369759 N Loss 12524 GPC6 20 114  chr14 23862374 23888040 N Loss 25666 MYH6, MYH7, 20 MIR208B 115  chr14 28506099 28520243 N Loss 14144 between BC148262 20 and CR597916 116  chr14 32904231 32909169 N Gain 4938 AKAP6 20 117  chr14 33859159 33860185 N Gain 1026 NPAS3 11 118  chr14 37928753 37948391 N Loss 19638 MIPOL1 15 119  chr14 68068610 68071772 N Loss 3162 5′ of PIGH 15 120  chr15 33605301 33617521 N Gain 12220 RYR3 20 121  chr15 47518807 47527672 N Loss 8865 SEMA6D 16 122  chr15 58851369 58853307 N Gain 1938 LIPC 14 123  chr15 60074956 60103803 Y 5 Loss 28847 5′ of BNIP2 (90 kb) 20 124  chr15 66521832 66524433 N Loss 2601 MEGF11 17 125  chr15 87830530 87870489 N Loss 39959 between AGBL1, and 20 TMEM83, NTRK3 126  chr16 16245729 16256767 N Loss 11038 ABCC6, MRP6 34 127  chr16 21363810 21602618 N Loss 238808 More than 10 genes 25 128  chr16 82446255 82711504 Y 5 Gain 265249 CDH13 24 129  chr16 83909041 83926368 N Loss 17327 5′ of MLYCD, 3′ of 20 HSBP1 130  chr17 4007594 4324408 Y 4 Gain 316814 ZZEF1, KIAA0399, 20 CYB5D2, ANKFY1, UBE2G1, SPNS3  131** chr17 21556170 25363654 N Loss 3807484 BC070367, FAM27L, 20 BC039120, CR592140, CR592128 132  chr17 39211908 39221312 N Loss 9404 KRTAP2-4 15 133  chr17 64258845 64259329 N Loss 484 5′ of APOH and 5′ of 11 PRKCA 134  chr18 30037470 30037675 N Loss 205 FAM59A 10 135  chr20 4234781 4238447 N Gain 3666 5′ of ADRA1D 16 136  chr20 6013320 6017259 N Loss 3939 CRLS1/DKFZp762C112 14 137  chr20 15755244 15765167 N Loss 9923 MACROD2 20 138  chr20 47337049 47341312 N Gain 4263 PREX1 14 139  chr20 49132410 49132637 N Loss 227 PTPN1 10 140  chr20 56248075 56252910 N Loss 4835 PMEPA1 20 141  chr21 17311697 17435462 N Loss 123765 5′ of C21orf34, 3′ of 20 USP25 142  chr21 42855515 42855647 Y 1 Gain 132 TMPRSS2 10 143  chr22 30731066 30731540 N Gain 474 SF3A1 10 144  chr22 33459104 33470309 N Loss 11205 5′ of SYN3 20 145  chr22 39515118 39525791 N Loss 10673 3′ of APOBECSH, 3′ of 20 CBX7 146  chr22 44251958 44257056 N Loss 5098 SULT4A1/SULTX3 19 147  chr22 44641315 44641594 N Gain 279 KIAA1644 10 148  chr22 51055900 51234443 Y 4 Gain 178543 ARSA, SHANK3, 10 BC050343, ACR, MGC70863, RABL2B 149  chrX 3206732 3216695 N Loss 9963 3′ of MXRA5, ARSF 19 150  chrX 57285994 57291268 N Gain 5274 5′ of FAAH2 11 151  chrX 133460586 133466162 N Loss 5576 5′ of PHF6 11 152  chrX 142769032 142781735 N Loss 12703 5′ of SLITRK4, 3′ of 15 SPANXN2 153  chrX 151041009 151042244 N Loss 1235 5′ of MAGEA4 12 Total = 2,642 Probes References: 1. Jacquemont et al., 2006 2. AGP, 2007 3. Sebat et al., 2007 4. Marshall et al., 2008 5. Christian et al., 2008 *Nos 16 & 26: includes overlapping literature CNVs **No. 131: Much of this region spans the centromere and is heterochromatic

TABLE 9 185 CNVs reportedly associated with ASD from published studies Custom CNV Origin iSelect CHOP Array No. CNV Regions (hg19, GRCh37) Literature Probes 1 chr1: 146626687-146641912 CHOP_CNV 208 2 chr1: 146644352-146646782 CHOP_CNV 208 3 chr1: 146649431-146651526 CHOP_CNV 208 4 chr1: 146655885-146661221 CHOP_CNV 208 5 chr1: 146714336-146767441 CHOP_CNV 208 6 chr1: 147013183-147042947 CHOP_CNV 208 7 chr1: 147119170-147142612 CHOP_CNV 208 8 chr1: 147191843-147211176 CHOP_CNV 208 9 chr1: 147228333-147245482 CHOP_CNV 208 10 chr1: 152538131-152539246 CHOP_CNV 22 11 chr1: 152551861-152552978 CHOP_CNV 22 12 chr1: 176233934-176277050 CHOP_CNV 20 13 chr2: 13202218-13248445 CHOP_CNV 20 14 chr2: 37208154-37311483 CHOP_CNV 20 15 chr2: 50147489-51240182 CHOP_CNV 84 16 chr2: 51267143-51294094 CHOP_CNV 62 17 chr2: 78414693-78457739 CHOP_CNV 20 18 chr2: 99858712-99871568 CHOP_CNV 17 19 chr2: 237821591-237832364 CHOP_CNV 94 20 chr3: 1940192-1940920 CHOP_CNV 10 21 chr3: 2573150-2573529 CHOP_CNV 11 22 chr3: 4224733-4261302 CHOP_CNV 20 23 chr3: 31702318-32023236 CHOP_CNV 20 24 chr3: 37903670-38025958 CHOP_CNV 20 25 chr3: 121343502-121387782 CHOP_CNV 20 26 chr3: 172231370-173116242 CHOP_CNV 116 27 chr3: 173116245-173254086 CHOP_CNV 100 28 chr3: 173271686-173289279 CHOP_CNV 100 29 chr3: 174001117-174885989 CHOP_CNV 100 30 chr4: 13656804-13932850 CHOP_CNV 20 31 chr4: 73756500-73905356 CHOP_CNV 60 32 chr4: 73920417-73935470 CHOP_CNV 60 33 chr4: 73940504-74124500 CHOP_CNV 60 34 chr4: 144627954-144635127 CHOP_CNV 11 35 chr5: 118229547-118343923 CHOP_CNV 100 36 chr5: 118407187-118469872 CHOP_CNV 100 37 chr5: 118478541-118584821 CHOP_CNV 100 38 chr5: 118604420-118730292 CHOP_CNV 100 39 chr5: 118730295-118856171 CHOP_CNV 100 40 chr6: 39071841-39082863 CHOP_CNV 20 41 chr6: 69235102-69237305 CHOP_CNV 10 42 chr6: 122793063-123047516 CHOP_CNV 34 43 chr6: 127440049-127518908 CHOP_CNV 20 44 chr6: 135818945-136037191 CHOP_CNV 20 45 chr6: 162664588-162667009 CHOP_CNV 31 46 chr6: 168349013-168596249 CHOP_CNV 20 47 chr7: 2649899-2654358 CHOP_CNV 20 48 chr7: 32700564-32804186 CHOP_CNV 20 49 chr7: 69064321-70257852 CHOP_CNV 23 50 chr7: 111502940-111846460 CHOP_CNV 20 51 chr7: 141695680-141806545 CHOP_CNV 20 52 chr8: 43646415-43657436 CHOP_CNV 20 53 chr8: 54858496-54907579 CHOP_CNV 20 54 chr9: 116111824-116132133 CHOP_CNV 86 55 chr9: 116135700-116139257 CHOP_CNV 85 56 chr9: 119187508-120177315 CHOP_CNV 58 57 chr9: 136501486-136524464 CHOP_CNV 37 58 chr10: 87359313-87944322 CHOP_CNV 105 59 chr10: 87951688-87959047 CHOP_CNV 79 60 chr10: 88126251-88893189 CHOP_CNV 104 61 chr10: 105353785-105615162 CHOP_CNV 20 62 chr10: 118350491-118368684 CHOP_CNV 20 63 chr12: 31409581-31410819 CHOP_CNV 13 64 chr12: 53183470-53189890 CHOP_CNV 20 65 chr12: 57345220-57352101 CHOP_CNV 20 66 chr12: 71833814-71980084 CHOP_CNV 20 67 chr13: 20977807-21100010 CHOP_CNV 20 68 chr14: 94184645-94254764 CHOP_CNV 20 69 chr15: 23686020-23692388 CHOP_CNV 19 70 chr15: 24842742-24979665 CHOP_CNV 47 71 chr15: 25101701-25223727 CHOP_CNV 53 72 chr16: 16243423-16317335 CHOP_CNV 40 73 chr16: 47276822-47330242 CHOP_CNV 20 74 chr16: 70954495-71007921 CHOP_CNV 20 75 chr16: 75572016-75590168 CHOP_CNV 20 76 chr16: 84599210-84610700 CHOP_CNV 40 77 chr17: 30819629-31203900 CHOP_CNV 20 78 chr17: 64298927-64806860 CHOP_CNV 31 79 chr18: 3498838-3880133 CHOP_CNV 20 80 chr19: 22639351-22639555 CHOP_CNV 10 81 chr19: 23835709-23870015 CHOP_CNV 38 82 chr19: 23926161-23941637 CHOP_CNV 38 83 chr19: 43225795-43440224 CHOP_CNV 20 84 chr19: 52880583-52901119 CHOP_CNV 108 85 chr19: 52901122-52909308 CHOP_CNV 108 86 chr19: 52909311-52921656 CHOP_CNV 108 87 chr19: 52932442-52934660 CHOP_CNV 108 88 chr19: 52934663-52942694 CHOP_CNV 108 89 chr19: 52956761-52961405 CHOP_CNV 108 90 chr20: 8113297-8865545 CHOP_CNV 40 91 chr20: 55993557-55997466 CHOP_CNV 33 92 chr22: 21021266-21028944 CHOP_CNV 19 93 chr22: 29999566-30094583 CHOP_CNV 20 94 chrX: 6966962-7066187 CHOP_CNV 20 95 chrX: 139998330-140335594 CHOP_CNV 71 96 chrX: 140335597-140443613 CHOP_CNV 71 97 chrX: 140590844-140672859 CHOP_CNV 71 98 chrX: 140677836-140678897 CHOP_CNV 71 99 chrX: 140713997-140714859 CHOP_CNV 71 100 chrX: 148663310-148669114 CHOP_CNV 60 101 chrX: 148676928-148678215 CHOP_CNV 60 102 chrX: 148678218-148713566 CHOP_CNV 60 103 chrX: 148858522-149097275 CHOP_CNV 60 104 chrX: 154719774-154842595 CHOP_CNV 40 105 chr1: 110230419-110236364 Literature_CNV 0 106 chr1: 146555186-147779086 Literature_CNV 152 107 chr1: 162573378-167543374 Literature_CNV 61 108 chr1: 230111830-232145817 Literature_CNV 43 109 chr2: 54076-1198908 Literature_CNV 23 110 chr2: 17406571-18378433 Literature_CNV 21 111 chr2: 32678416-33378738 Literature_CNV 40 112 chr2: 45455651-45984915 Literature_CNV 31 113 chr2: 50145644-51259671 Literature_CNV 84 114 chr2: 51979551-52401447 Literature_CNV 40 115 chr2: 57200002-61699998 Literature_CNV 98 116 chr2: 62258231-63028717 Literature_CNV 48 117 chr2: 115139568-115617934 Literature_CNV 20 118 chr2: 162387215-162840241 Literature_CNV 20 119 chr2: 198797484-209741388 Literature_CNV 119 120 chr2: 236632457-238435065 Literature_CNV 101 121 chr2: 238435068-242985349 Literature_CNV 125 122 chr3: 2028902-2884398 Literature_CNV 31 123 chr3: 11034422-11080933 Literature_CNV 20 124 chr3: 67656832-68957204 Literature_CNV 24 125 chr3: 100203669-100487283 Literature_CNV 20 126 chr3: 143608410-144494785 Literature_CNV 20 127 chr3: 195674002-197284998 Literature_CNV 27 128 chr4: 154087652-172339893 Literature_CNV 191 129 chr5: 176990003-180905258 Literature_CNV 42 130 chr6: 13889303-15153950 Literature_CNV 24 131 chr7: 23876-1297908 Literature_CNV 16 132 chr7: 15386880-15538756 Literature_CNV 20 133 chr7: 72576596-75922729 Literature_CNV 42 134 chr7: 83144216-86082367 Literature_CNV 40 135 chr7: 87999366-89294562 Literature_CNV 24 136 chr7: 121210655-121381762 Literature_CNV 40 137 chr7: 121755766-122152424 Literature_CNV 40 138 chr7: 128907065-128998138 Literature_CNV 20 139 chr7: 152589804-152616097 Literature_CNV 20 140 chr8: 6264122-6506023 Literature_CNV 20 141 chr8: 53271330-53555369 Literature_CNV 20 142 chr9: 7735282-7770231 Literature_CNV 20 143 chr9: 38027602-38298598 Literature_CNV 20 144 chr9: 102472181-136065177 Literature_CNV 464 145 chr10: 13049365-13367445 Literature_CNV 20 146 chr10: 46269076-50892143 Literature_CNV 64 147 chr10: 50892146-51450787 Literature_CNV 32 148 chr10: 84158614-89685463 Literature_CNV 178 149 chr11: 40329226-40653822 Literature_CNV 20 150 chr13: 23604102-24794298 Literature_CNV 23 151 chr13: 35516457-36246870 Literature_CNV 20 152 chr13: 48083039-48475962 Literature_CNV 20 153 chr13: 67572852-67762297 Literature_CNV 20 154 chr15: 20266959-25480660 Literature_CNV 123 155 chr15: 25582397-25684125 Literature_CNV 28 156 chr15: 73090002-76507998 Literature_CNV 44 157 chr15: 85105976-85708062 Literature_CNV 20 158 chr16: 2097991-2138710 Literature_CNV 20 159 chr16: 6052837-6260813 Literature_CNV 20 160 chr16: 14982501-16482497 Literature_CNV 64 161 chr16: 21534307-21901307 Literature_CNV 48 162 chr16: 21901310-22703860 Literature_CNV 34 163 chr16: 29671216-30173786 Literature_CNV 20 164 chr16: 82195236-82722082 Literature_CNV 40 165 chr17: 9964035-10361280 Literature_CNV 20 166 chr17: 14139846-15282723 Literature_CNV 23 167 chr17: 48646233-48704540 Literature_CNV 20 168 chr18: 32073255-35145997 Literature_CNV 42 169 chr19: 27896698-28805250 Literature_CNV 20 170 chr20: 127914-419869 Literature_CNV 20 171 chr20: 2837196-4006397 Literature_CNV 23 172 chr20: 8044044-8527513 Literature_CNV 30 173 chr20: 41602847-41867105 Literature_CNV 20 174 chr21: 37412682-37622182 Literature_CNV 20 175 chr22: 18640348-21461644 Literature_CNV 51 176 chr22: 38368320-38380536 Literature_CNV 20 177 chr22: 47956883-49122331 Literature_CNV 36 178 chr22: 49405478-49971756 Literature_CNV 29 179 chr22: 51113071-51171638 Literature_CNV 36 180 chrX: 94421-5469456 Literature_CNV 78 181 chrX: 5808084-5999993 Literature_CNV 20 182 chrX: 28605682-29974014 Literature_CNV 25 183 chrX: 53300002-53699998 Literature_CNV 20 184 chrX: 70364712-70391048 Literature_CNV 20 185 chrX: 153213010-153399998 Literature_CNV 40 Total = 4,492 probes* *Note that there is significant redundancy in this probe set, as many of the literature CNVs included on the array overlapped.

TABLE 10 25 CNVs identified from single nucleotide variants (SNVs) on custom array Gain or Validation Start Coord. End Coord. No. CNV Source Loss Status Chromosome (hg19) (hg19) Gene(s) 1 SequenceSNP Loss PASS chr7 93070811 93116320 CALCR MIR653 MIR489 2 SequenceSNP Gain PASS chr14 100705631 100828134 SLC25A29 YY1 MIR345 SLC25A47 WARS 3 SequenceSNP Gain PASS chr14 102018946 102026138 DIO3AS DIO3OS 4 SequenceSNP Loss PASS chr14 102729881 102749930 MOK/RAGE 5 SequenceSNP Gain PASS chr14 102973910 102975572 ANKRD9 6 SequenceSNP Gain PASS chr15 25690465 26793077 ATP10A MIR4715 GABRB3 LOC503519 LOC100128714 7 SequenceSNP Gain PASS chr15 27184517 27216737 GABRA5 GABRG3 8 SequenceSNP Gain PASS chr15 28408312 28513763 HERC2 9 SequenceSNP Loss PASS chr15 31092983 31369123 FAN1 TRPM1 MTMR10 MIR211 TRPM1 10 SequenceSNP Gain/Loss PASS chr15 31776648 31822910 OTUD7A 11 SequenceSNP Gain PASS chr20 32210931 32441302 NECAB3 CBFA2T2 E2F1 C20orf134 ZNF341 C20orf144 PXMP4 ZNF341 CHMP4B 12 SequenceSNP Gain No data chr14 99640708 99642376 BCL11B 13 SequenceSNP Loss FAIL chr3 176755900 176782811 TBL1XR1 14 SequenceSNP Gain FAIL chr7 100159979 100456457 MOSPD3 TFR2 LOC100129845 GIGYF1 GNB2 LRCH4 ACTL6B FBXO24 PCOLCE AGFG2 SAP25 POP7 GIGF1 ZAN SLC12A9 EPHB4 15 SequenceSNP Gain/Loss FAIL chr7 149481075 149576256 SSPO ATP6V0E2 ZNF862 LOC401431 16 SequenceSNP Gain FAIL chr14 24507010 24550497 DHRS4L1 LRRC16B NRL CPNE6 17 SequenceSNP Loss FAIL chr14 96758018 96777946 ATG2B 18 SequenceSNP Gain FAIL chr14 100995537 101010301 BEGAIN WDR25 19 SequenceSNP Gain FAIL chr14 103986349 104182224 TRMT61A CKB TRMT61A BAG5 APOPT1 C14orf153 XRCC3 KLC1 ZFYVE21 20 SequenceSNP Gain FAIL chr15 30000877 30033536 TJP1 21 SequenceSNP Gain FAIL chr15 40544493 40661306 C15orf56 PAK6 PLCB2 C15orf52 DISP2 22 SequenceSNP Gain FAIL chr15 42139583 42302433 JMJD7-PLA2G4B PLA2G4B SPTBN5 EHD4 PLA2G4E 23 SequenceSNP Loss FAIL chr15 56243611 56258744 NEDD4 24 SequenceSNP Gain FAIL chr20 35234192 35444437 NDRG3 TGIF2-C20ORF24 C20orf24 SLA2 DSN1 KIAA0889 25 SequenceSNP Gain FAIL chr20 57268867 57290347 NPEPL1 STX16-NPEPL1

Example 2 Design of a Custom Clinical Array

A custom clinical array was designed based on the results of the study described in Example 1. The study array used in Example 1 included about 10,000 probes for the regions being studied. Therefore, a custom array was specifically designed for clinical use to enhance coverage for the CNVs identified as associated with ASD. Custom probes for detection of other childhood developmental delay disorders were also included on the array as outlined in Table 11 below.

Table 11 below summarizes the custom probes designed for and included on the clinical array. The clinical array is based on the Affymetrix CytoScan-HD array and includes the 83,443 custom probes provided in the accompanying sequence listing. The 83,443 probes were added to the Affymetrix array to ensure sufficient coverage of all of the regions described in Tables 8 and 9, as well as to detect CNVs for the other disorders listed in Table 11.

TABLE 11 Summary of Custom Probes Custom CNV Disorder CNV source Probes Autism Literature CNVs 58950 Utah CNVs 3691 CHOP CNVs 2619 Utah familial sequence variants Rett syndrome 28 Noonan/Costello/CFC syndromes 0 Tuberous sclerosis 0 ADHD 8764 DD 9364 Tourette syndrome 27 Dyslexia 0 Total 83443

A description of the custom probes as summarized in Table 11 is provided in Table 14 of U.S. Provisional Application 61/977,462 and Table 14 from International PCT Publication No. 2014/055915, the disclosure of each of which is incorporated by reference in their entireties. Table 14 from these disclosures provides the following information: The third column, labeled “hg19 Coordinates/Gene Name”, displays the genome coordinates (hg19) of the CNV for which each probe was designed. The second column, labeled “EXPOS” displays the nucleotide position within the chromosomal region shown in the third column that represents the center of the oligonucleotide probe. The oligonucleotides themselves are 25 nucleotides in length, so the center is nucleotide 13. The first column lists the SEQ ID NO for the oligonucleotide (DNA probe) which is provided in the accompanying sequence listing.

Tables 12 and 13 below list the CNVs identified in the study described in Example 1 (from Tables 3 and 4), and further include the SEQ ID NOs for the custom probes, where applicable. Since custom probes were only included on the array for some CNVs identified in Example 1, N/A is used to denote that no custom probes were used. Sequences of the custom probes are set forth in the sequence listing as SEQ ID NOs:1-83,443. As noted above, the positions of the probes are described in Table 14 of U.S. Provisional Application 61/977,462 and Table 14 of International PCT Publication No. 2014/055915, the disclosure of each of which is incorporated by reference in their entireties.

TABLE 12 Summary of Custom Probes for CNVs from Table 3 Custom Probe No. CNV Region - Replication Cohort Gene/Region SEQ ID NOs¹ 1 chr1: 145703115-145736438 CD160, PDZK1 N/A 2 chr1: 215854466-215861792 USH2A 27,988-28,001 3 chr2: 51266798-51339236 upstream of NRXN1 32,494-32,587 4 chr3: 172591359-172604675 downstream of SPATA16 N/A 5 chr4: 189084240-189117031 downstream of TRIML1 N/A 6 chr6: 7461346-7470321 between RIOK1 and DSP 62,966-62,998 7 chr6: 62426827-62472074 KHDRBS2 N/A 8 chr6: 147577803-147684318 STXBP5 N/A 9 chr7: 6870635-6871412 upstream of CCZ1B 69,319-69,561 10 chr7: 93070811-93116320 CALCR, MIR653, MIR489 N/A 11 chr9: 28207468-28348133 LINGO2 N/A 12 chr9: 28354180-28354967 LINGO2 (intron) N/A 13 chr10: 83886963-83888343 NRG3 (intron) N/A 14 chr10: 92262627-92298079 downstream of BC037970 N/A 15 chr12: 102095178-102108946 CHPT1 7410-7426 16 chr13: 40089105-40090197 LHFP (intron) N/A 17 chr14: 100705631-100828134 SLC25A29, YY1, MIR345, N/A SLC25A47, WARS 18 chr14: 102018946-102026138 DIO3AS, DIO3OS N/A 19 chr14: 102729881-102749930 MOK N/A 20 chr14: 102973910-102975572 ANKRD9 (RAGE) N/A 21 chr15: 25690465-28513763 ATP10A, GABRB3, N/A GABRA5, GABRG3, 22 chr15: 31092983-31369123 FAN1, MTMR10, MIR211, N/A TRPM1 23 chr15: 31776648-31822910 OTUD7A N/A 24 chr20: 32210931-32441302 NECAB3, CBFA2T2, N/A C20orf144, NECAB3, ¹Custom probes were only included on the array for some CNVs. N/A denotes that no custom probes were used.

TABLE 13 Summary of Custom Probes for CNVs from Table 4 Custom Probe No. Region of Highest Significance Gene/Region SEQ ID NOs¹ 1 chr1: 146656292-146707824 FMO5 N/A 2 chr2: 13203874-13209245 upstream of LOC100506474 31,283-31,314 3 chr2: 45489954-45492582 between UNQ6975 and N/A SRBD1 4 chr2: 51237767-51245359 NRXN1** N/A 5 chr2: 62230970-62367720 COMMD1 33,402-39,860 6 chr2: 115133493-115140263 between LOC440900 and N/A DPP10** 7 chr3: 1937796-1941004 between CNTN6 and N/A CNTN4** 8 chr3: 67657429-68962928 SUCLG2, FAM19A4, N/A FAM19A1 9 chr4: 73766964-73816870 COX18, ANKRD17 51,803-52,100 10 chr4: 171366005-171471530 between AADAT** and N/A HSP90AA6P 11 chr5: 118527524-118589485 DMXL1, TNFAIP8 61,165-61,290 12 chr6: 39069291-39072241 SAYSD1 64,149-64,167 13 chr8: 54855680-54912001 RGS20, TCEA1 N/A 14 chr10: 49370090-49471091 FRMPD2P1, FRMPD2 N/A 15 chr10: 50884949-50943185 OGDHL, C10orf53 N/A 16 chr12: 53177144-53180552 between KRT76 and KRT3 N/A 17 chr15: 20192970-20197164 downstream of HERC2P3 12,508-12,563 18 chr15: 25099351-25102073 SNRPN** N/A 19 chr15: 25099351-25102073 SNRPN** N/A 20 chr15: 25579767-25581658 between SNORD109A and N/A UBE3A** 21 chr15: 25582882-25662988 UBE3A** N/A 22 chr16: 21958486-22172866 C16orf52, UQCRC2**, N/A PDZD9, VWA3A 23 chr16: 29664753-30177298 DOC2A**, ASPHD1, N/A LOC440356, TBX6, LOC100271831, PRRT2 CDIPT, QPRT, YPEL3, PPP4C, MAPK3**, SPN, MVP, FAM57B, ZG16, ALDOA, INO80E, SEZ6L2, TAOK2, KCTD13, MAZ, KIF22, GDPD3, C16orf92, C16orf53, TMEM219, C16orf54, HIRIP3 24 chr16: 82423855-82445055 between MPHOSPH6 and N/A CDH13 25 chr17: 14132271-14133349 between COX10 and N/A CDRT15 26 chr17: 14132271-15282708 PMP22**, CDRT15, TEKT3, N/A MGC12916, CDRT7, HS3ST3B1 27 chr17: 14952999-15053648 between CDRT7 and PMP22 N/A 28 chr17: 15283960-15287134 between TEKT3 and N/A FAM18B2-CDRT4 29 chr20: 8162278-8313229 PLCB1** N/A 30 chrX: 29944502-29987870 IL1RAPL1** N/A 31 chrX: 140329633-140348506 SPANXC N/A 32 chrX: 148882559-148886166 MAGEA8 N/A ¹Custom probes were only included on the array for some CNVs. N/A denotes that no custom probes were used.

Example 3 Use of CNV Data to Select Patients for Treatment with Mitochondrial Therapies

In this study, collective CNV data were used to assess a patient population having diagnoses for autism and/or developmental delay. The population was stratified into groups most likely to respond well to pharmacotherapies in development for mitochondrial disease patients or currently available mitochondrial therapies. The collective CNV data was obtained using the custom clinical array as described in Example 2.

At the time of the study, there were 77 mitochondrial disease-associated nuclear-encoded genes, and 1805 human nuclear mitochondrial genes listed in the NIH Pubmed database with the tag “Mitochondria.”

The patient population consisted of 1,740 patients undergoing clinical evaluation of autism spectrum disorders and/or other disorders of childhood development. Of the 1,740 patients tested, 1,176 patients were evaluated using the Affymetrix Cytoscan HD array or the Affymetrix Cytogenetics 2.7 M array, and 564 were tested using a custom clinical array generated as described above in Example 2. The diagnostic yield of the custom clinical array of clinically reportable copy number variants (CNVs) was 28.9%. Diagnostic yield is the percentage of patients with a clinically relevant CNV divided by the total number of patients tested.

The custom clinical array used herein had the highest probe density of all marketed CMA platforms, and contains probes that provide high enough resolution to detect CNVs affecting a single gene in 45 of the 77 mitochondrial disease-associated nuclear-encoded genes known at the time of the study. It is the only CMA platform with sufficient probe density to detect 4 of these 45 genes.

Size of deletion in CNVs was determined in the following manner. All probes on the custom microarray represent a known chromosomal coordinate based on hg19. See the sequence listing and Table 14 from U.S. Provisional Application 61/977,462 and Table 14 from International PCT Publication No. 2014/055915, the disclosure of each of which is incorporated by reference in their entireties. In an individual who has no deletion or duplication in a particular region, all probes will have a uniform signal that represents having 2 copies of each chromosome at that position. A CNV is detected by looking for increases (duplication) or decreases (deletion) in signal intensity at individual probes, each of which represent a unique location in the genome. When 25 or more probes targeting contiguous regions of the genome show a reduced signal compared to an individual with no CNV, the test individual can then be said to have a deletion at the location containing the probes that have a reduced signal. Since the genomic coordinates of each probe are known, CNV size is determined by the coordinates of the probes showing reduced signal intensity, and the maximal CNV boundaries are defined by the probes nearest to those showing reduced signal that themselves do not show a reduced signal.

In this study, 27 patients, or 1.5% of the patient population, had clinically relevant CNVs that affect mitochondrial disease-associated genes. Furthermore, 185 patients, or 11% of the patient population, had a CNV affecting one or more of the 1805 nuclear genes encoding proteins associated with mitochondrial functions. These patients were further sorted into groups based on the mitochondrial function carried out by genes within their CNVs (Table 15). In Table 15, the chromosome number of the deletion or duplication for each patient is shown, followed by the list of nuclear mitochondrial genes affected by the CNV. One third of these 185 patients had changes in genes involved with electron transport functions or other functions related to regulating oxidative stress. These patients comprise the group most likely to respond to EPI-743 as well as other therapies aimed at relieving oxidative stress.

TABLE 15 Patients identified with changes in mitochondrial genes Chromosome Patient location of DEL or Number CNV DUP Affected Mitochondrial Genes (*mitochondrial disease-associated genes in bold) 1 chr1 DUP DAP3 LMNA SEMA4A SLC25A44 MEF2D MRPL24 NTRK1 MRPS21P2 CCDC19 KCNJ10 (Patient 1, continued) CASQ1 PEA15 PPOX NDUFS2 TOMM40L SDHC 2 chr13 DEL DNAJC15 ENOX1 TPT1 SLC25A30 TIMM9P3 SUCLA2 RB1 ATP5F1P1 MRPS31P5 THSD1P1 (Patient 2, continued) MRPS31P4 SLC25A5P4 3 chr15 DUP EIF2AK4 BMF IVD MRPL42P5 RAD51 RMDN3 C15orf62 NDUFAF1 PLA2G4B ATP5HP1 (Patient 3, continued) CKMT1B STRC CKMT1A 4 chr16 DUP TUFM ATP2A1 SPNS1 5 chr17 DUP AIPL1 ALOX12 ACADVL SLC2A4 PLSCR3 TMEM102 6 chr17 DUP ALOX12 ACADVL SLC2A4 PLSCR3 TMEM102 TP53 WRAP53 7 chr17 DUP COX10 8 chr17 DUP COX10 9 chr17 DUP TTC19 PLD6 FLCN NT5M PEMT ATPAF2 MYPO15A MIEF2 SHMT1 ALDH3A2 (Patient 9, continued) AKAP10 TMEM11 MAP2K3 MTRNR2L1 10 chr18 DUP TYMS ENOSF1 SLC25A3P3 NDUFV2 RALBP1 CIDEA AFG3L2 11 chr2 DUP RNASEH1 CMPK2 RSAD2 YWHAQ DDX1 HADHA HADHB OTOF SLC35F6 MPV17 (Patient 11, continued) ZNF513 MRPL33 BRE TRMT61B C2orf71 NLRC4 12 chr2 DEL IDH1 ACADL CPS1 ERBB4 13 chr20 DUP MTRNR2L3 PCK1 VAPB TUBB1 ATP5E SLMO2-ATP5E MRPS16P2 MTG2 MIR1-1 PRPF6 14 chr22 DEL PPARA TRMU GRAMD4 MAPK12 MAPK11 SCO2 TYMP CPT1B 15 chr22 DEL MAPK12 MAPK11 SCO2 TYMP CPT1B 16 chr22 DEL MAPK12 MAPK11 SCO2 TYMP CPT1B 17 chr3 DEL SUCLG2 18 chr3 DEL MRPL3 ACAD11 TF PCCB LOC100289118 19 chrX DUP HCCS LOC100422628 MRPL35P4 ATXN3L CA5B PDHA1 SMPX ACOT9 PDK3 GK (patient 19, continued) CYBB RPGR OTC MPC1L DDX3X ATP5G2P4 MAOA MAOB FUNDC1 DUSP21 LOC392452 RP2 NDUFB11 LOC101060049 MRPL32P1 HDAC6 TIMM17B PQBP1 PIM2 LOC101060199 HSD17B10 LOC100128454 LOC100288560 APEX2 ALAS2 MTRNR2L10 LOC644924 GRPEL2P2 LOC100128171 OPHN1 PIN4 LOC100129272 ABCB7 COX7B ATP7A POU3F4 APOOL MRPS22P1 PABPC5 TSPAN6 NOX1 TIMM8A ARMCX3 LOC100420247 SLC25A53 PRPS1 PSMD10 ACSL4 AGTR2 MRPS17P9 SLC25A43 SLC25A5 NDUFA1 GLUD2 MRRFP1 XIAP APLN AIFM1 SLC25A14 TIMM8BP2 LOC100422685 FATE1 BCAP31 ABCD1 IDH3G MECP2 TAZ TMLHE 20 chrX DUP HCCS LOC100422628 MRPL35P4 ATXN3L CA5B PDHA1 SMPX ACOT9 PDK3 GK (Patient 20, continued) CYBB RPGR OTC MPC1L DDX3X ATP5G2P4 MAOA MAOB FUNDC1 DUSP21 LOC392452 RP2 NDUFB11 LOC101060049 MRPL32P1 HDAC6 TIMM17B PQBP1 PIM2 LOC101060199 HSD17B10 LOC100128454 LOC100288560 APEX2 ALAS2 MTRNR2L10 LOC644924 21 chrX DEL OTC 22 chrX DUP TAZ 23 chr2 DUP PTCD3 IMMT MRPL35 REEP1 24 chr6 DUP MUT 25 chr5 DEL MCCC2 26 chr9 DEL GLDC 27 chr9 DUP GLDC Genes involved in redox reactions in mitochondria, but not (yet) associated with disease NDUF* (NADH dehydrogenase ubiquinone) 28 chr16 DUP MRPS34 HAGH FAHD1 NDUFB10 GFER E4F1 ECI1 29 chr16 DUP MRPS34 HAGH FAHD1 NDUFB10 GFER E4F1 ECI1 30 chr19 DUP NDUFA3 PRPF31 31 chr21 DUP NRIP1 MRPL39 ATP5J GABPA APP SOD1 ITSN1 ATP5O MRPS6 RUNX1 (Patient 31, continued) ATP5J2LP MRPL20P1 TIMM9P2 NDUFV3 MRPL51P2 C21orf33 C21orf2 IMMTP1 SLC19A1 S100B 32 chr22 DUP SLC25A5P1 SMDT1 NDUFA6 CYP2D6 CYB5R3 ATP5L2 BIK MCAT TSPO 33 chr7 DEL NDUFA4 ATP5* (F1 Complex) 34 chr14 DUP INF2 SIVA1 AKT1 ATP5G1P1 35 chr16 DEL ATP5A1P3 DHODH DHX38 36 chr17 DUP ATP5LP6 37 chr21 DEL ATP5J2LP MRPL20P1 38 chr3 DUP ATP5G1P3 39 chr3 DEL TNFSF10 ATP5G1P4 40 chr4 DEL WFS1 GRPEL1 HTRA3 PROM1 PPARGC1A ATP5LP3 SOD3 41 chrY DUP TOMM22P2 ATP5JP1 MRP63P10 DDX3Y TOMM22P1 SLC25A15P1 42 chrY DUP TOMM22P2 ATP5JP1 MRP63P10 DDX3Y TOMM22P1 SLC25A15P1 43 chrY DUP TOMM22P2 ATP5JP1 MRP63P10 DDX3Y TOMM22P1 SLC25A15P1 44 chrY DUP TOMM22P2 ATP5JP1 MRP63P10 DDX3Y TOMM22P1 SLC25A15P1 Cytochrome c reductase 45 chr1 DEL AKT3 COX20 46 chr11 DUP SIRT3 COX8BP MRPS24P1 RNH1 HRAS MIR210 TALDO1 SLC25A22 CTSD MRPL23 (Patient 46, continued) IGF2 INS CDKN1C PHLDA2 STIM1 47 chr19 DUP RDH13 TNNI3 COX6B2 48 chr17 DUP COA3 BECN1 VAT1 DHX8 NAGS SLC25A39 GFAP NMT1 MAPT 49 chr16 DEL UQCRC2 50 chr16 DEL UQCRC2 51 chr8 DEL CYP11B1 CYP11B2 TOP1MT CYC1 Mitochondrial solute/metabolite carriers 52 chr17 DUP SLC2A4 PLSCR3 TMEM102 TP53 WRAP53 53 chr2 DUP SLC3A1 54 chr2 DUP SLC25A12 55 chr22 DEL PRODH SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 56 chr22 DEL PRODH SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 57 chr22 DUP PRODH SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 58 chr22 DUP PRODH SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 59 chr22 DUP PRODH SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 60 chr22 DEL PRODH SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 61 chr22 DEL PRODH SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 62 chr22 DEL PRODH SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 63 chr22 DEL PRODH SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 64 chr22 DEL SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 65 chr22 DEL SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 66 chr17 DUP TIMM22 67 chr3 DUP SLC25A26 68 chrX DEL MRPS17P9 SLC25A43 Mitochondrial ATPases/Energy Metabolism 69 chr1 DEL AURKAIP1 MRPL20 ATAD3C ATAD3B ATAD3A PRKCZ 70 chr9 DUP LOC138234 AK3 GLDC LOC138864 71 chr9 DEL LOC138234 AK3 GLDC Thioredoxin 72 chr1 DUP TXNIP PDZK1 73 chr1 DEL TXNIP PDZK1 Ribosomal Complex Proteins 74 chr10 DEL BNIP3 ECHS1 MTG1 CYP2E1 75 chr16 DEL MPG HBA2 PDIA2 MRPL28 76 chr17 DUP MYO19 MRM1 77 chr17 DUP MYO19 MRM1 78 chr2 DUP TIMM8AP1 IFIH1 79 chr6 DEL MRPS18B DHX16 80 chr7 DEL MRPS17 Creatine Kinase 81 chr15 DEL CKMT1B STRC 82 chr15 DEL CKMT1B STRC Apoptosis related 83 chr12 DEL GABARAPL1 BCL2L14 DDX47 84 chr15 DUP DUT 85 chr10 DUP VDAC2 86 chr16 DUP WWOX 87 chr16 DEL WWOX 88 chr16 DEL WWOX 89 chr17 DUP YWHAE 90 chr2 DEL BCL2L11 MERTK 91 chr2 DUP BCL2L11 MERTK 92 chr22 DEL CHEK2 HSCB 93 chr3 DUP FHIT 94 chr3 DUP FHIT 95 chr3 DUP FHIT LOC101060206 96 chr3 DEL FHIT 97 chr9 DUP NAIF1 SLC25A25 98 chr2 DUP PRKCE Glutathione S transferase family 99 chr12 DEL MGST1 LOC390298 Maturation of OXPHOS proteins 100 chr13 DEL MIPEP Protection from Oxidative Stress 101 chr16 DUP MPV17L NDE1 102 chr16 DUP MPV17L NDE1 103 chr16 DUP MPV17L NDE1 104 chr16 DUP MPV17L NDE1 105 chr16 DUP MPV17L NDE1 106 chr16 DUP MPV17L NDE1 107 chr16 DEL MPV17L NDE1 108 chr16 DUP MPV17L NDE1 109 chr16 DUP MPV17L NDE1 110 chr16 DUP MPV17L NDE1 111 chr16 DUP MPV17L NDE1 112 chr16 DEL CA5A 113 chr22 DEL PRODH SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 114 chr22 DEL PRODH SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 115 chr22 DUP PRODH SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 116 chr22 DUP PRODH SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 117 chr22 DUP PRODH SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 118 chr22 DEL PRODH SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 119 chr22 DEL PRODH SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 120 chr22 DEL PRODH SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 121 chr22 DEL PRODH SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 122 chr22 DEL SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 123 chr22 DEL SLC25A1 MRPL40 C22orf29 TXNRD2 AIFM3 124 chr2 DEL OLA1 125 chr4 DEL SPATA18 NOA1 POLR2B 126 chr8 DEL IL7 MRPS28 DECR1 CALB1 127 chr16 DUP MAPK3 (?) 128 chr16 DEL MAPK3 (?) 129 chr16 DEL MAPK3 (?) 130 chr16 DEL MAPK3 (?) 131 chr16 DUP MAPK3 (?) 132 chr16 DEL MAPK3 (?) 133 chr16 DUP MAPK3 (?) 134 chr16 DEL MAPK3 (?) 135 chr16 DEL CREBBP (?) 136 chr22 DEL MAPK1 (?) 137 chr22 DEL MAPK1 (?) Mitochondrial Fatty Acid Synthesis 138 chr16 DUP ACSF3 SPG7 TUBB3 139 chr2 DUP GPAT2 STARD7 TMEM127 SNRNP200 Mitochondrial nucleotidase 140 chr17 DEL PLD6 FLCN NT5M 141 chr2 DUP RNASEH1 ABC (ATP Binding Cassette) Transporters 142 chr17 DEL ABCA8 143 chr2 DUP ABCA12 144 chr7 DUP TMEM243 ABCB4 ABCB1 Heme biosynthesis 145 chr3 DUP CPOX Humanin Family of Mitochondrial Peptides 146 chr5 DUP MTX3 MTRNR2L2 Mitochondrial maintenance 147 chr6 DUP PARK2 148 chr7 DUP MAD1L1 NUDT1 149 chr7 DEL CHCHD3 150 chr8 DUP MICU3 Immune Response 151 chr7 DUP EZH2 4p- Cohort 153 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT WFS1 GRPEL1 HTRA3 PROM1 154 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT WFS1 GRPEL1 HTRA3 PROM1 155 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT WFS1 GRPEL1 HTRA3 156 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT WFS1 GRPEL1 HTRA3 PROM1 157 chr4 DEL PDE6B ATP5I LETM1 NAT8L 158 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT 159 chr4 DEL PDE6B ATP5I LETM1 NAT8L 160 chr4 DEL PDE6B ATP5I 161 chr4 DEL PDE6B ATP5I LETM1 NAT8L 162 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT 163-de- chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT WFS1 GRPEL1 HTRA3 PROM1 PPARGC1A ceased (Patient 163, continued) ATP5LP3 SOD3 MRPL51P1 164 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT 165 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT WFS1 GRPEL1 HTRA3 PROM1 166 chr4 DEL PDE6B ATP5I 167 chr4 DEL PDE6B ATP5I LETM1 NAT8L 168 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT WFS1 GRPEL1 HTRA3 169 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT 170 chr4 DEL PDE6B ATP5I LETM1 NAT8L 171 chr4 DEL PDE6B ATP5I LETM1 172 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT WFS1 GRPEL1 HTRA3 173 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT WFS1 GRPEL1 HTRA3 174 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT WFS1 175 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT 176 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT WFS1 GRPEL1 HTRA3 PROM1 177 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT 178 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT WFS1 GRPEL1 HTRA3 179 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT 180 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT WFS1 GRPEL1 181 chr4 DEL PDE6B ATP5I LETM1 NAT8L HTT 182 chr4 DEL LETM1 183 chr4 DEL LETM1 NAT8L HTT WFS1 GRPEL1 HTRA3 184 chr4 DEL LETM1 NAT8L HTT 185 chr4 DEL LETM1

In this study, a genetically well-defined patient cohort was identified, that would benefit from EPI-743 or other mitochondrial pharmacotherapy (Table 15). This cohort represents 11% of the patient population, a surprising frequency since these patients were not selected for testing based on a suspicion of mitochondrial dysfunction but rather based on generalized clinical symptomology of ASD and/or other disorders of childhood development. The estimated incidence of mitochondrial disease in the general population is about 1 in 10,000. In addition to these patients' genotypes, the available phenotypic data in the form of doctor-reported ICD-9 codes for these patients encompass an array of traits that significantly overlap with phenotypic characteristics of children diagnosed with mitochondrial disease who have already been shown to be excellent responders to EPI-743 (Table 16). These phenotypic characteristics also overlap with the phenotypic traits exhibited by autistic patients and patients with other developmental disorders. This overlap can lead to doctors diagnosing a patient with an ASD rather than with a mitochondrial disease.

TABLE 16 Doctor-reported ICD-9 codes for patients with CNVs affecting nuclear mitochondrial genes Patient ICD-9 ICD-9 No. (Primary listed) Other 1 0 237.70 - Neurofibromatosis, unspecified 2 0 279.11 - DiGeorge Syndrome 3 0 279.11 - DiGeorge Syndrome 4 0 315.39 - Other developmental speech or language disorder 5 0 315.9 - Unspecified delay in development 6 0 315.9 - Unspecified delay in development 7 0 315.9 - Unspecified delay in development 8 0 315.9 - Unspecified delay in development 9 0 333.99 - Other extrapyramidal diseases and abnormal movement disorders 10 0 348.30 - Encephalopathy, unspecified 11 0 758.39 - Other autosomal deletions 12 0 780.39 - Other Convulsions 13 0 783.42 - Delayed Milestones 14 0 783.42 - Delayed Milestones 15 0 783.42 - Delayed Milestones 16 0 783.42 - Delayed Milestones 17 0 279.49 - Autoimmune disease, not elsewhere classified, 279.9 - Unspecified disorder of immune mechanism 18 0 299.01 - Autistic disorder, residual state, 345.1 - Generalized convulsive epilepsy 19 0 315.39 - Other developmental speech or language disorder, 783.40 - Lack of normal physiological development, unspecified 20 0 315.9 - Unspecified delay in development, 780.39 - Other convulsions 21 0 315.9 - Unspecified delay in development, 780.39 - Other convulsions 22 0 315.9 Unspecified delay in development, 783.42 - Delayed milestones 23 0 343.9 - Infantile cerebral palsy, unspecified, 758.39 - Other autosomal deletions 24 0 438.10 - Late effects of cerebrovascular disease, speech and language deficit, unspecified, 438.0 - Late effects of cerebrovascular disease, cognitive deficits, 728.9 - Unspecified disorder of muscle, ligament, and fascia, 300.00 - Anxiety state, unspecified, 314.01 - Attention deficit disorder with hyperactivity 25 0 745.2 - Tetralogy of fallot, 335.0 - Werdnig-Hoffmann disease, 386.19 - Other peripheral vertigo 26 0 749.00 - Cleft palate, unspecified; 744.9 - Unspecified congenital anomalies of face and neck 27 0 779.7 - Periventricular leukomalacia, 335.0 - Werdnig-Hoffmann disease 28 0 780.39- Other convulsions, 783.40 - Lack of normal physiological development, unspecified 29 0 780.39 - Other convulsions, 758.9 - Conditions due to anomaly of unspecified chromosome, 279.00 - Hypogammaglobulinemia, unspecified 30 0 783.40 - Lack of normal physiological development, unspecified, 728.9 - Unspecified disorder of muscle, ligament, and fascia 31 0 783.40 - Lack of normal physiological development, unspecified, 783.43 - short stature, 749.23 - Cleft palate with cleft lip, bilateral, complete 32 0 783.42 - Delayed milestones, 781.3 - Lack of coordination 33 0 783.42 - Delayed milestones, 783.40 - Lack of normal physiological development, unspecified 34 0 783.42 - Delayed milestones, 426.11 - First degree atrioventricular block, 378.9 - Unspecified disorder of eye movements 35 0 784.69 - Other symbolic dysfunction, 744.9 - Unspecified congenital anomalies of face and neck, 749.02 - Cleft palate, unilateral, incomplete 36 0 795.2 - Nonspecific abnormal findings on chromosomal analysis, 783.1 - Abnormal weight gain 37 0 v18.9 - Family history of genetic disease carrier 38 0 786.09 - Other respiratory abnormalities, v71.02 - Observation for childhood or adolescent antisocial behavior, 760.71 - Alcohol affecting fetus or newborn via placenta or breast milk 39 0 335.0 - Werdnig-Hoffmann disease 40 299.00-Autism, current or active 0 41 299.00-Autism, current or active 0 42 299.00-Autism, current or active 0 43 299.00-Autism, current or active 0 44 299.00-Autism, current or active 0 45 299.00-Autism, current or active 0 46 299.00-Autism, current or active 0 47 299.00-Autism, current or active 0 48 299.00-Autism, current or active 0 49 299.00-Autism, current or active 0 50 299.00-Autism, current or active 0 51 299.00-Autism, current or active 0 52 299.00-Autism, current or active 0 53 299.00-Autism, current or active 0 54 299.00-Autism, current or active 0 55 299.00-Autism, current or active 0 56 299.00-Autism, current or active 0 57 299.00-Autism, current or active 0 58 299.00-Autism, current or active 0 59 299.00-Autism, current or active 0 60 299.00-Autism, current or active 0 61 299.00-Autism, current or active 0 62 299.00-Autism, current or active 0 63 299.00-Autism, current or active 0 64 299.00-Autism, current or active 0 65 299.00-Autism, current or active 0 66 299.00-Autism, current or active 0 67 299.00-Autism, current or active 299 68 299.00-Autism, current or active 315.9 69 299.00-Autism, current or active 315.9 70 299.00-Autism, current or active 315.9 71 299.00-Autism, current or active 756 72 299.00-Autism. current or active 758.32 73 299.00-Autism, current or active 758.9 74 299.00-Autism, current or active 783.42 75 299.00-Autism, current or active 349.82, 768.72, 348.30 76 299.00-Autism, current or active 780.39, 315.9 77 299.00-Autism, current or active; 0 312.9-Behavior/Conduct disorder 78 299.00-Autism, current or active; 345 312.9-Behavior/Conduct disorder 79 299.00-Autism, current or active; 0 312.9-Behavior/Conduct disorder; 319.0-Unspecified mental retardation 80 299.00-Autism, current or active; 0 312.9-Behavior/Conduct disorder; 345- Gen. nonconvulsive epilepsy; 742.1- Microcephaly 81 299.00-Autism, current or active; 0 312.9-Behavior/Conduct disorder; 781.2-Gait abnormality 82 299.00-Autism, current or active; 0 315.5-Mixed developmental disorder 83 299.00-Autism, current or active; 0 315.8-Other specified delays in dev.; 783.42-Delayed-Milestones 84 299.00-Autism, current or active; 0 315.9-Unspecified delay in development 85 299.00-Autism, current or active; 781.3 315.9-Unspecified delay in development 86 299.00-Autism, current or active; 315.39 315.9-Unspecified delay in development; 319.0-Unspecified mental retardation 87 299.00-Autism, current or active; 0 315.9-Unspecified delay in development; 319.0-Unspecified mental retardation; 759.7-Multiple congenital anomalies 88 299.00-Autism, current or active; 780.39, 334.3 319.0-Unspecified mental retardation 89 299.00-Autism, current or active; 0 319.0-Unspecified mental retardation; 345-Gen. nonconvulsive epilepsy 90 299.00-Autism, current or active; 345- 0 Gen. nonconvulsive epilepsy 91 299.00-Autism, current or active; 345- 0 Gen. nonconvulsive epilepsy 92 299.00-Autism, current or active; 0 759.83-Fragile X syndrome 93 312.9-Behavior/Conduct disorder 0 94 312.9-Behavior/Conduct disorder 0 95 312.9-Behavior/Conduct disorder 0 96 312.9-Behavior/Conduct disorder 758.81 97 312.9-Behavior/Conduct disorder 315.9, 756.0, 348.0 98 312.9-Behavior/Conduct disorder; 783.42 314.01-ADHD 99 312.9-Behavior/Conduct disorder; 0 319.0-Unspecified mental retardation 100 312.9-Behavior/Conduct disorder; 0 759.7-Multiple congenital anomalies; 783.42-Delayed-Milestones 101 312.9-Behavior/Conduct disorder; 0 781.0-Abnormal involuntary movements 102 314.01-ADHD; 315.2-Other specific 311, 783.40 learning difficulti 103 314.01-ADHD; 315.9-Unspecified 0 delay in development; 759.7-Multiple congenital anomalies 104 315.4-Coordination disorder: 781.3 Clumsiness; 315.9-Unspecified delay in development 105 315.4-Coordination disorder: 0 Clumsiness; 728.9-Hypotonia 106 315.8-Other specified delays in dev. 0 107 315.8-Other specified delays in dev. 335 108 315.8-Other specified delays in dev. 335.0, 745.2 109 315.9-Unspecified delay in 0 development 110 315.9-Unspecified delay in 0 development 111 315.9-Unspecified delay in 728.85 development 112 315.9-Unspecified delay in 744.9-Dysmorphic features development 113 315.9-Unspecified delay in 0 development; 319.0-Unspecified mental retardation 114 315.9-Unspecified delay in 348.3 development; 345.5-Simple Partial Seizures/Epilepsy 115 315.9-Unspecified delay in 781.3 development; 742.1-Microcephaly 116 315.9-Unspecified delay in 0 development; 759.7-Multiple congenital anomalies 117 315.9-Unspecified delay in 0 development; 783.41-Failure-to-Thrive 118 315.9-Unspecified delay in 0 development; 783.42-Delayed- Milestones 119 319.0-Unspecified mental retardation 0 120 319.0-Unspecified mental retardation 0 121 319.0-Unspecified mental retardation 0 122 319.0-Unspecified mental retardation 0 123 319.0-Unspecified mental retardation 0 124 319.0-Unspecified mental retardation 0 125 319.0-Unspecified mental retardation 0 126 319.0-Unspecified mental retardation 0 127 319.0-Unspecified mental retardation 742.3 128 319.0-Unspecified mental retardation 783.42 129 319.0-Unspecified mental retardation 348.3, 780.39 130 319.0-Unspecified mental retardation; 0 345.9-Epilepsy, unspecified; 759.7- Multiple congenital anomalies 131 319.0-Unspecified mental retardation; 0 345.9-Epilepsy, unspecified; 759.7- Multiple congenital anomalies 132 319.0-Unspecified mental retardation; 0 345.9-Epilepsy, unspecified; 759.7- Multiple congenital anomalies 133 319.0-Unspecified mental retardation; 0 345.9-Epilepsy, unspecified; 759.7- Multiple congenital anomalies 134 319.0-Unspecified mental retardation; 0 345.9-Epilepsy, unspecified; 759.7- Multiple congenital anomalies 135 319.0-Unspecified mental retardation; 0 345.9-Epilepsy, unspecified; 759.7- Multiple congenital anomalies 136 319.0-Unspecified mental retardation; 0 759.7-Multiple congenital anomalies 137 319.0-Unspecified mental retardation; 0 759.7-Multiple congenital anomalies 138 319.0-Unspecified mental retardation; 0 759.7-Multiple congenital anomalies 139 319.0-Unspecified mental retardation; 0 759.7-Multiple congenital anomalies 140 319.0-Unspecified mental retardation; 0 759.7-Multiple congenital anomalies 141 319.0-Unspecified mental retardation; 0 759.7-Multiple congenital anomalies 142 319.0-Unspecified mental retardation; 0 759.7-Multiple congenital anomalies 143 319.0-Unspecified mental retardation; 586 759.7-Multiple congenital anomalies 144 319.0-Unspecified mental retardation; 780.39 759.7-Multiple congenital anomalies 145 319.0-Unspecified mental retardation; 780.39 759.7-Multiple congenital anomalies 146 319.0-Unspecified mental retardation; 780.39 759.7-Multiple congenital anomalies 147 319.0-Unspecified mental retardation; 780.39 759.7-Multiple congenital anomalies 148 319.0-Unspecified mental retardation; 780.39 759.7-Multiple congenital anomalies 149 319.0-Unspecified mental retardation; 780.39 759.7-Multiple congenital anomalies 150 319.0-Unspecified mental retardation; 780.39 759.7-Multiple congenital anomalies 151 319.0-Unspecified mental retardation; 780.39 759.7-Multiple congenital anomalies 152 345-Gen. nonconvulsive epilepsy 742.2 153 345-Gen. nonconvulsive epilepsy; 318.0, 315.34 742.1-Microcephaly; 759.7-Multiple congenital anomalies 154 345.4-Complex Partial 0 Seizures/Epilepsy 155 345.6-Infantile spasms 0 156 345.9-Epilepsy, unspecified; 759.7- 315.9 Multiple congenital anomalies 157 356.1-Charcot-Marie-Tooth disease 315.9, 158 728.9-Hypotonia 0 159 728.9-Hypotonia 0 160 728.9-Hypotonia 315.9 161 728.9-Hypotonia 783.42 744.9 530.81 162 728.9-Hypotonia 783.42, 728.5 163 728.9-Hypotonia; 742.1-Microcephaly; 0 781.2-Gait abnormality 164 728.9-Hypotonia; 759.7-Multiple 0 congenital anomalies; 781.2-Gait abnormality 165 728.9-Hypotonia; 759.81-Prader-Willi 783.40, syndrome 166 742.1-Microcephaly 378.9, 783.42 167 742.1-Microcephaly 783.42; 787.20; 530.81 168 742.3-Congenital hydrocephalus 0 169 742.3-Congenital hydrocephalus; 783.42 742.4-Other specified anomalies of brain 170 742.4-Other specified anomalies of 0 brain 171 742.4-Other specified anomalies of 783.4 brain 172 759.7-Multiple congenital anomalies 315.9 173 759.7-Multiple congenital anomalies 315.9 174 759.7-Multiple congenital anomalies 315.9 175 759.7-Multiple congenital anomalies 315.9 176 759.7-Multiple congenital anomalies 315.9 177 759.7-Multiple congenital anomalies 315.9 178 759.7-Multiple congenital anomalies 758.9 179 759.7-Multiple congenital anomalies 783.42 180 759.7-Multiple congenital anomalies 315.9, 358.8 181 759.89-Other specified congenital F45.22 anomal 182 783.42-Delayed-Milestones 0 183 783.42-Delayed-Milestones 315.31 184 783.42-Delayed-Milestones 783.40, 752.61 185 784.3-Aphasia 315.9

Example 4 Phenotype:Genotype Correlations in Subjects with Syndromic Conditions

CNV data were used to discover new phenotypic correlations associated with specific genotypes, in particular, in patients with syndromic forms of autism and/or developmental delay. These correlations have predictive value in that children with similar CNVs tend to have similar co-morbid conditions as well as similar responses to treatments, thereby allowing caregivers the ability to alter and enhance medical treatment plans based on this new knowledge. Specifically, in this study, children with 4p-Syndrome, also known as Wolf-Hirschhorn Syndrome (WHS), were assessed. However, the methods described here can be generalized to any of the many syndromic microduplication or microdeletion conditions that arise from localized CNVs of variable lengths and phenotypes.

A custom, 2.8M-probe, chromosomal microarray platform (CMA) to finely map CNVs was employed in this study. Probes used in the CMA are provided in the sequence listing and the chromosomal regions to which these probes maps can be found at Table 14 of U.S. Provisional Application 61/977,462 and Table 14 from International PCT Publication No. 2014/055915, the disclosure of each of which is incorporated by reference in their entireties.

Size of deletion in CNVs was determined in the following manner. All probes on the custom microarray represent a known chromosomal coordinate based on hg19. See the sequence listing and Table 14 from U.S. Provisional Application 61/977,462 and Table 14 from International PCT Publication No. 2014/055915, the disclosure of each of which is incorporated by reference in their entireties. In an individual who has no deletion or duplication in a particular region, all probes will have a uniform signal that represents having 2 copies of each chromosome at that position. A CNV deletion is detected by looking for decreases (deletion) in signal intensity at individual probes, each of which represent a unique location in the genome. When 25 or more probes targeting contiguous regions of the genome show a reduced signal compared to an individual with no CNV, the test individual can then be said to have a deletion at the location containing the probes that have a reduced signal. Since the genomic coordinates of each probe are known, CNV size is determined by the coordinates of the probes showing reduced signal intensity, and the maximal CNV boundaries are defined by the probes nearest to those showing reduced signal that themselves do not show a reduced signal.

Wolf-Hirschhorn Syndrome is a rare, multi-genetic disorder that is characterized by a variety of different clinical features. Presentation of the disorder includes: intellectual disability, failure to thrive, seizures, and a characteristic craniofacial facies. The degree to which these “classic” features as well as other co-morbid conditions present themselves in each patient can vary significantly, thereby requiring that the medical management of this disorder be tailored to an individual's needs. Without the benefit of genetic correlation studies of this syndrome, standard medical care for Wolf-Hirschhorn patients means the running of expensive and sometimes invasive medical tests for each patient in order to determine the best course of action. The extent of the chromosomal deletion on the short arm of chromosome 4 is a crucial determining factor for both the severity and the range of phenotypes presented in individuals, but this data is often missed when a diagnosis is made based on the results of a FISH (fluorescence in situ hybridization) test (Ji et al., Chin Med J (Engl) 2010; Maas et al., J. Med Genet. 2008). This FISH test can only indicate the presence or absence of a specific “critical” locus on chromosome 4p, not the size or extent of the deletion. Nor can it detect the presence or absence of any other CNV in the genome. The custom array described herein addresses these needs.

The goal of this study was to examine data from approximately 48 patients with Wolf-Hirschhorn Syndrome and apply novel algorithmic techniques to determine correlations between the patients' finely mapped genetic deletions and their parent-reported phenotypes. This was the largest correlation study to date of phenotypes and treatment outcomes of Wolf-Hirschhorn Syndrome that utilizes genetic data from a customized fine-mapping microarray (as described above in Example 2), at 1 kb resolution.

The patient cohort for this study is provided in the table below.

Patient Cohort for Study Set Forth in Example 5 Total Participants 48 Female:Male (27:21) Average Age: 11 years (Range: 1-38 years Size of 4p- deletion 1.3-33.9 Mb Number of genes in deletion 28-207 Initial diagnosis Karotype/FISH: 63% (30/48) Patients with second CNV 29% (14/48) Average size of second CNV 4.7 Mb

To score phenotypic data, parent-reported answers to a questionnaire to capture information on >20 different features were used. Correlations between genotypes and phenotypes were observed. Candidate loci were identified using Genome Browser and Ingenuity IPA software. Specifically, patient data was obtained through a partnership with the 4p-Support Group, a nationally run, parent-founded organization, who collected clinical data in the form of a questionnaire called a BioForm, which is completed by member families on a voluntary basis. Data on the Bioform included specific questions about congenital heart disease, renal anomalies that can lead to kidney failure, skeletal dysmorphic features, and other medical conditions that commonly affect this population's medical management and quality of life. The Bioform also collected data concerning parents' experiences with pharmacological and other types of treatments for their child's seizures, which can be severe and life-threatening.

FIG. 5 illustrates the correlation between deletion size and number of clinical features present in the study cohort. The number of patient-family reported clinical features increased with increasing deletion size. Individuals with the 5 smallest deletions had on average 6.2 clinically relevant features compared to individuals with the 5 largest deletions, who had 10.0 clinically relevant features (up to 40% more clinically relevant features based on size of deletion). This correlation suggests that CMA detection, as opposed to FISH technology, has predictive value in the quantity and quality, of clinical manifestations that arise depending on deletion size.

FIG. 6 shows that number of genes in the 4p deletion and the number of phenotypes scored are positively correlated. The deletion size (FIG. 5) and genetic content (FIG. 6) of the deletion uncovered by CMA positively correlates with the number of clinical features of WHS that manifest. This can change medical management of the patient, particularly in terms of symptoms that can be best ameliorated by early detection and treatment (vision loss, seizures, kidney failure).

A second CNV elsewhere in the genome, which co-occurs with a 4p-deletion −30% of the time, increases the number of co-morbid features. Moreover, a second CNV increases the likelihood of having potentially life-threatening status epilepticus (SE) seizures (11/27, or 40%, of individuals with pure deletions report having SE, versus 7/10 individuals with an additional CNV report having SE). Therefore, the CMA can detect second CNVs that co-occur with a 4p deletion. These second CNVs average less than 5 Mb in size, which is below the detection of karyotype and can only be detected by FISH if the second CNV is suspected and specifically probed for. Taken together, this means that by using karyotype/FISH technologies, the second CNV is often missed. Presence of a second CNV correlates with the number of clinical features that manifest, again potentially affecting medical management of the individual. For example, as provided above, the presence of a second CNV increases the chances that the individual may have life-threatening seizures of the status epilepticus type, requiring immediate administration of anti-seizure meds and ER support (to monitor breathing).

Individuals with interstitial deletions not including the terminal 751 kb do not report having seizures (n=4), whereas deletions that encompass the terminus correlate well with seizures (100%).

There are 12 genes in the 751 kb terminal region defined by our work (use of our CMA) that, when lost, correlate with presence of seizures, and when present, correlate with lack of seizures. These candidates lead to the possibility of developing targeted treatments for seizures in these individuals (90% of whom have seizures). Therefore, the position of the CNV in the 4p region, as determined by CMA, is important for medical management and patient prognosis.

One additional individual with a larger interstitial deletion reported having exactly one febrile seizure in 8 years and has been advised by the physician to not take seizure medication since there appears to be little risk. There are 12 genes in this region; of these, bioinformatics analyses indicate PIGG (Phosphotidylinositol glycan anchor biosynthesis, class G) as a candidate seizure-susceptibility gene when deleted along with the WHS critical region(s). Mutations in other members of the GPI anchor biosynthesis pathway cause autosomal recessive disorders (e.g., Mabry Syndrome), all of which have seizures.

FIG. 8 illustrates the correlation of CMA data with a specific type of clinical manifestation, in this case, congenital heart disease. Each bar on the graph represents the size and location of a patient's 4p-deletion as detected by the customized array provided herein. Black bars indicate patients with congenital heart disease. Gray bars represent patients without congenital heart disease. As shown in FIG. 8, patients with a deletion of 6 MB or larger were more likely to have congenital heart disease than those who had smaller deletions.

In addition, patients with an additional CNV finding elsewhere in the genome, in addition to the deletion of the 4p terminus, were far more likely to have a debilitating, life-threatening condition known as status epilepticus. Multiple CNV findings occur in about 30% of WHS patients, a significant fraction of the affected population. Patients with status epilepticus are at risk of having prolonged seizures that can lead to death if not taken to an emergency room quickly, within minutes of seizure onset. The knowledge of an increased risk of having a status epilepticus seizure can therefore allow caregivers to prescribe preventative medications as well as respond to seizures quickly. As shown in FIG. 9, patients with multiple CNV findings were more likely to have status epilepticus than patients with only the 4p-deletion. Each horizontal bar on the graph represents the size and location of a patient's 4p-deletion as detected by the customized array provided herein. Black bars indicate patients with status epilepticus. Gray bars represent patients without status epilepticus.

Sophisticated algorithmic tools are used to mine other potential clinical correlations with CNV results. For example, detailed data on over twenty clinical features, including renal disease, intellectual disability, developmental delay, seizures, vision loss and blindness, and other conditions affecting ear, skin, teeth and skeletal development have been collected.

The results of the study have wide-ranging implications for the care of patients affected with Wolf-Hirschhorn syndrome, including better understanding of the genetic causes for certain key features of the syndrome; refining medical practice guidelines for patients based on genetic correlates leading to time-saving and cost-saving measures for both patient families and the insurance industry; defining of best parent-reported treatments for seizures based on patient genotypes; and more broadly, development of powerful software tools and algorithms that can better correlate multiple genes and phenotypes with one another.

Example 5 Identification of Best Responders to Mechanistic Drug Therapies

In this study, CNV data were used to identify groups of patients who represent best candidate responders to new mechanism-directed autism drugs in development and on the market. The patient population was stratified into groups that were predicted to respond well to glutamatergic and GABAergic drugs, and those patients that were likely to either not respond or to fare poorly in response to a drug, due to underlying genetics. The approach described in this study has wide-ranging applications to other pharmacotherapies aimed at any genetic disorder detectable by the customized array provided herein, as long as the pharmacotherapy is mechanism-based and the molecular pathways involved are roughly known. In this way, the customized array platform provided herein is a powerful means of delivering personalized medicine: the right drug in the right dose to the right person at the right time, based on genetic knowledge.

Recent developments in the understanding of the etiology of autism indicate that the genetic contribution to this disorder could be as high as 90%. This ‘genetic contribution’ is largely comprised of genes involved in establishing, maintaining and regulating the function of the neural synapse. Furthermore, genetic and electrophysiological studies indicate that autism may arise from an imbalance between excitatory and inhibitory signaling in the brain. In fact, studies using genetic mouse models of autism indicate that key features of autism can arise from either of two scenarios: too much excitatory signaling in the brain, or too little. Drugs are now in development targeted to correct the imbalance. Several drug companies have candidates in various stages of clinical trial development aimed at this mechanism.

Many different genetic changes can lead to the same set of autism-related phenotypes. If imbalance of the excitatory/inhibitory system leads to autism, then one must first determine which side of the imbalance a patient is on, in order for mechanistic drug therapy can be effective and safe. Furthermore, certain forms of autism may arise from mechanisms only peripherally associated with synaptic signaling imbalances, and entirely different pharmacotherapies might be more appropriate for these cases. Decades of studies of drugs that affect glutamatergic signaling in the laboratory indicate that drugs and electrical stimulations that over-excite glutamatergic neurons can lead to hallucinations, seizures and in the worst cases, irreparable neurologic damage and neural cell death. Too little excitatory response, on the other hand, leads to sedation, and a host of other potentially negative side effects.

Table 17 provides predictions for drug responses based on specific genetic changes detectable by the customized array provided herein.

TABLE 17 Predictions for drug response based on genetics Disorders mGluR5 mGluR5 which can be antagonist or agonist or clinically GABA(B) GABA(B) distinguishable receptor receptor Gene from ASD agonist antagonist Ref FMR1 Fragile X Yes No Whalley, 2012 (review) TSC1/2 Tuberculosis No Yes Auerbach, 2011 Shank3 Phelan- No Yes Verpelli, 2011 McDermid Syndrome SAPAP3 Autism/DD Yes Wan, 2011 (probably) Densin180 Autism/DD Yes Carlisle, 2011 (probably) GRM5 ADHD No Yes, if inferred GRM5/+

Table 18 shows the results of querying the 1,400+ patients with CNV results in the database provided herein for CNVs with changes in known glutamatergic/GABAergic signaling genes. 28% of “Abnormal” cases were findings with some relevance to mGluR5/GABA pathway functions. The following were identified: 6 Fragile X patients, 5 Williams-Beuren Syndrome patients, 6 DiGeorge Syndrome patients, 2 Angelman syndrome patients, and 1 each of Rubenstein-Taybi Syndrome, Legius syndrome, Phelan-McDermid Syndrome, CDKL5 deletion, CASK deletion, and EDNRB deletion. These patients, therefore, represent the best candidates for a clinical trial for the use of a glutamate receptor or GABA receptor targeted drug. The effect of the CNV deletion or duplication on excitatory or inhibitory activity of their neurons determines whether an agonist or antagonist is most appropriate.

TABLE 18 Chromosome location (gene Associated condition/ Specific role in GABA, glutamatergic, of Interest) clinical features Incidence Genes or synapse 7q811.23 Williams syndrome Prevalence ~1 in 7,500 (Many) Curr Opin Neurol, 2012 April; 25(2); 112-24 to 1 in 20,000 births 7q11.23 7q11.23 duplication (Many) Curr Opin Neurol, 2012 April; 25(2); 112-24 syndrome, ASD 15q11.2 Neurodevelopmental ~1 per 12,000-20,000 GABRB3, FMRP/mGluR pathway (UBE3A) disorder/autism Angelman syndrome GABRG3, spectrum disorder/ GABRA5, Angelman syndrome/ SNRPN, Prader-Willi syndrome UBE3A 15q13.3 15q13.3 deletion or 1 in 100001 in 20000 CHRNA7 Loss leads to lower GAD-65 expression in (CHRNA7) duplication syndrome hippocampus of het. mice. Adams et al, Neuroscience. 2012 Apr. 5; 207: 274-82. 15q21 Hirschprung Disease 1 in 5000 to 1 in 10000 EDNRB endothelin receptor type B receives ET-1 (EDNRB) Type II (all Hirschprung) signal for oxytocin-containing magnocellular neurons in the SON to release glutamate J. Neurosci 2010 Dec. 15; 30(50): 16855-63; they down-regulate glial glutamate transporters in injured brain Brain Pathol, 2004 October; 14(4): 406-14 22q11.2 DiGeorge syndrome 2 estimated incidence of (Many) Altered dosage of one, or several 22q11 (Velocardiofacial one in 4000 births mitochondrial genes, particularly during syndrome 2) early post-natal cortical development, may disrupt neuronal metabolism or synaptic signaling Mol Cell Neurosci. 2008; GABA(B) receptor subunit 1 binds to proteins affected in 22q11 deletion syndrome. Zunner D, 2010 March 22q13.31q13.33 22q13.3 deletion There are SHANK3 Glut/GABA Synapse stability (SHANK3) syndrome approximately 600 (Phelan-McDermid reported cases of syndrome) Phelan- McDermid Syndrome worldwide 15q.14 Legius Syndrome Unknown, often SPRED1 Spred1 is a negative regulator of (SPRED1) misdiagnosed as NH Ras/Mapk/ERK; required for synaptic plasticity and hippocampus-dependent learning. J Neurosci. 2008 Dec. 31; 28(53): 14443-9 16p13.3 Rubinstein-Taybi Prevalence ~1 per CREBBP Downstream effector of mGluR type 1 (CREBBP) syndrome 10,000 live births receptors in LTP/synaptic plasticity; J Neurosci. 2012 May Xp11.4 XLID and FG syndrome Unknown, several CASK In complex with NEGNs/NRXNs (CASK) hundred cases worldwide Xq28 Rett syndrome/MECP2- ~1 in 10,000 females MECP2 FMRP/mGluR pathway (MECP2) related conditions (similar, numbers to ALS, Huntington's, and Cystic Fibrosis)

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The various embodiments described above can be combined to provide further embodiments. All of the U.S. patents, U.S. patent application publications, U.S. patent application, foreign patents, foreign patent application and non-patent publications referred to in this specification and/or listed in the Application Data Sheet are incorporated herein by reference, in their entirety. Aspects of the embodiments can be modified, if necessary to employ concepts of the various patents, application and publications to provide yet further embodiments.

These and other changes can be made to the embodiments in light of the above-detailed description. In general, in the following claims, the terms used should not be construed to limit the claims to the specific embodiments disclosed in the specification and the claims, but should be construed to include all possible embodiments along with the full scope of equivalents to which such claims are entitled. Accordingly, the claims are not limited by the disclosure. 

1. A method for assessing the presence or absence of a chromosomal deletion or duplication syndrome in a subject, comprising: probing a sample obtained from the subject for the presence or absence of one or more copy number variants (CNVs) associated with the chromosomal deletion or duplication syndrome, wherein the probing step comprises, mixing the sample with five or more oligonucleotides that are substantially complementary to portions of the genomic DNA sequence associated with the deletion or duplication syndrome under conditions suitable for hybridization of the five or more oligonucleotides to their complements or substantial complements; detecting whether hybridization occurs between the five or more oligonucleotides to their complements or substantial complements, or a subset thereof; obtaining hybridization values of the sample based on the detecting step; comparing the hybridization values of the sample to reference hybridization value(s) from at least one training set comprising hybridization value(s) from a sample that is positive for the one or more CNVs, or hybridization value(s) from a sample that is negative for the one or more CNVs, wherein the comparing step comprises determining a correlation between the hybridization values obtained from the sample and the hybridization value(s) from the at least one training set; determining whether the one or more CNV(s) is present or absent based on the comparing step; assessing whether the subject has the chromosomal deletion or duplication syndrome based on the determination of whether the one or more CNV(s) is present or absent.
 2. The method of claim 1, wherein the chromosomal deletion or duplication syndrome is selected from the syndromes set forth in Table A and Table B.
 3. The method of claim 1, wherein the chromosomal region associated with the deletion or duplication syndrome is selected from one of the chromosomal locations set forth in Table A or Table B.
 4. The method of claim 1, wherein the chromosomal deletion or duplication syndrome is associated with deletion or duplication of a mitochondrial associated gene.
 5. The method of claim 4, wherein the mitochondrial associated gene is selected from one or more of the genes in Table
 15. 6. The method of any one of claims 1-5, wherein the five or more oligonucleotides comprise from about 20 to about 2,000 oligonucleotides, from about 20 to about 1,500 oligonucleotides, from about 20 to about 1,000 oligonucleotides, from about 20 to about 750 oligonucleotides, from about 20 to about 500 oligonucleotides, from about 20 to about 250 oligonucleotides, or from about 20 to about 100 oligonucleotides.
 7. The method of any one of claims 1-5, wherein the five or more oligonucleotides comprise 20 or more oligonucleotides, 25 or more oligonucleotides, 30 or more oligonucleotides or 50 or more oligonucleotides.
 8. The method of any one of claims 1-7, wherein the sample comprises restriction digested double stranded DNA obtained from genomic DNA fragments; restriction digested single stranded DNA obtained from genomic DNA fragments; amplified restriction digested genomic DNA single stranded fragments; amplified restriction digested genomic DNA double stranded fragments; or a combination thereof.
 9. The method of claim 8, wherein the sample is free of histone proteins.
 10. The method of claim 8 or 9, wherein the amplified restriction digested genomic DNA single stranded fragments comprise a detectable label chemically attached to individual single stranded fragments.
 11. The method of any one of claims 8-10, wherein the amplified restriction digested genomic DNA single stranded fragments further comprise adapter sequences.
 12. The method of claim 11, wherein the adapter sequences are introduced via adapter-specific primers.
 13. The method of any one of claims 1-12, further comprising selecting the subject for chromosomal deletion or duplication syndrome therapy.
 14. The method of any one of claims 1-13, further comprising measuring the size of the one or more CNVs if the one or more CNVs is present in the sample obtained from the subject.
 15. The method of any one of claims 1-14, wherein the five or more oligonucleotides are bound to a solid state substrate.
 16. The method of claim 15, wherein the solid state substrate is a glass slide, a silicon wafer or a bead.
 17. The method of any one of claims 1-16, further comprising measuring the size of the one or more CNVs if the one or more CNVs is present in the sample obtained from the subject.
 18. The method of claim 17, comprising selecting the subject for therapy if the CNV is present, and is at least about 500 bases in length.
 19. The method of any one of claims 1-18, wherein the one or more CNVs comprise five to fifty CNVs set forth in Table
 15. 20. The method of claim 13 or 18, wherein the subject is selected for treatment with gene therapy, RNA interference (RNAi), behavioral therapy, music therapy, physical therapy, occupational therapy, sensory integration therapy, speech therapy, the Picture Exchange Communication System (PECS), dietary treatment, or drug therapy.
 21. The method of claim 20, wherein the behavioral therapy is selected from Applied Behavior Analysis (ABA), Discrete Trial Training (DTT), Early Intensive Behavioral Intervention (EIBI), Pivotal Response Training (PRT), Verbal Behavior Intervention (VBI), and Developmental Individual Differences Relationship-Based Approach (DIR), or a combination thereof.
 22. The method of claim 20, wherein the drug therapy is selected from antipsychotics, anti-depressants, anticonvulsants, stimulants, aripiprazole, guanfacine, selective serotonin reuptake inhibitors (SSRIs), riseridone, olanzapine, naltrexone, or a combination thereof.
 23. The method of any one of claims 1-18, wherein the chromosomal deletion or duplication syndrome is Wolf-Hirschhorn syndrome (WHS).
 24. The method of claim 13 or 18, wherein the one or more CNVs is associated with a mitochondrial associated gene and the therapy comprises administration to the subject EPI-743, antioxidants, Oxygen, arginine, Coenzyme Q10, idebenone, benzoquinone therapeutics, or a combination thereof.
 25. The method of claim 13 or 18, wherein the one or more CNVs is associated with a glutamate or GABA receptor gene and the therapy comprises administration to the subject a glutamate receptor agonist or antagonist or a GABA receptor agonist or antagonist.
 26. The method of claim 25, wherein the subject is selected for therapy with a glutamatergic receptor agonist or GABAergic antagonist if the effect of the CNV is an inhibitory effect, and wherein the subject is administered a glutamatergic receptor antagonist or GABAergic agonist if the effect of the CNV is an excitatory effect.
 27. The method of any one of claims 1-26, wherein the sample comprises polymerase chain reaction (PCR) amplified restriction digested genomic DNA single stranded fragments.
 28. The method of claim 27, wherein the PCR amplified restriction digested genomic DNA single stranded fragments comprise a detectable label chemically attached to individual single stranded fragments.
 29. The method of claim 28, wherein the amplified restriction digested genomic DNA single stranded fragments further comprise adapter sequences.
 30. The method of claim 29, wherein the adapter sequences are introduced via adapter-specific primers.
 33. The method of any one of claims 28-30, wherein the detectable label is a fluorescent label, enzyme label, radioisotope, chemiluminescent label, electrochemiluminescent label, bioluminescent label, polymer, polymer particle, metal particle, hapten, dye, or a combination thereof.
 34. The method of claim 33, wherein the detectable label is a fluorescent label.
 35. The method of claim 23, comprising selecting the patient for therapy if the deletion on the 4p chromosome is greater than or equal to 500 bases in length.
 36. The method of claim 23, comprising selecting the patient for therapy if the deletion on the 4p chromosome is greater than or equal to 1000 bases in length.
 37. The method of claim 23, comprising selecting the patient for therapy if the deletion on the 4p chromosome is greater than or equal to 1 Mb in length.
 28. The method of claim 34, wherein the fluorescent label is selected from 5-(and 6)-carboxyfluorescein, 5- or 6-carboxyfluorescein, 6-(fluorescein)-5-(and 6)-carboxamido hexanoic acid, fluorescein isothiocyanate, rhodamine, tetramethylrhodamine, and dyes such as Cy2, Cy3, and Cy5, optionally substituted coumarin including AMCA, PerCP, phycobiliproteins including R-phycoerythrin (RPE) and allophycoerythrin (APC), Texas Red, Princeton Red, green fluorescent protein (GFP) and analogues thereof, conjugates of R-phycoerythrin or allophycoerythrin, inorganic fluorescent labels such as particles based on semiconductor material like coated CdSe nanocrystallites, or a combination thereof. 